We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. We're tinkers, coders, and problem solvers . And we make it happen. Better products. Smarter platforms. And better ways of working. Working in Tech at Sky means building what's next - from automation platforms that keep Sky Q reliable, to tools that help engineers ship safely at scale. We're looking for a Senior Automation Engineer to help us evolve our Python based automation frameworks, CI/CD pipelines and tooling that power the Sky Q experience. You'll use your engineering craft to remove friction, increase quality, and enable teams to deliver features to millions of customers with confidence. What you'll do Design, build and maintain Python-based automation frameworks and tools that support end-to-end testing and operational workflows for Sky Q services. Develop, extend and optimise CI/CD pipelines (primarily in Jenkins) to ensure fast, reliable and repeatable delivery of software into multiple environments. Work hands on in Linux environments , scripting, configuring and troubleshooting automation jobs, agents and infrastructure to keep pipelines healthy and scalable. Collaborate with product engineering teams maintaining our Django and React applications , embedding automation into their workflows and improving observability and reliability. Introduce and integrate new tooling - including AI assisted development and test tools - to improve developer productivity, coverage and feedback cycles. Champion engineering best practices across the squad: code reviews, pair programming, clean code, robust testing strategies and continuous improvement. Act as a technical go to for automation , mentoring other engineers and helping shape the roadmap for our automation and test platforms. What you'll bring Advanced Python engineering capability - deep, hand s - on experience designing, building and maintaining robust automation frameworks using clean, modular, well tested code. High proficiency with CI/CD (Jenkins, Pipelines, CasC ) - able to architect, optimise, and troubleshoot complex pipelines, agents and integrations in large scale delivery environments. Strong Linux / VM operational expertise - confident working across distributed systems, debugging services, managing environments, and resolving complex infrastructure issues. Experience supporting or building web-based systems (e.g. Django backends and React frontends) and integrating them into automated pipelines. Solid competency in database operational support - capable of maintaining database related workflows, debugging data issues and supporting services used within automated pipelines. Competent API development experience - able to develop or extend backend APIs (e.g., Django/DRF) and integrate them seamlessly into automated workflows. Good awareness and some practical experience with AI a ssisted engineering workflows - such as using LLMs for automation tasks, applying ML assisted testing techniques, or experimenting with MCP style tooling to enhance productivity. Experience working effectively within Agile delivery teams - contributing to cross functional collaboration, communicating clearly, and supporting shared outcomes. An inclination toward continuous improvement - proactively seeking better ways of working, improving reliability, and helping raise engineering standards across the team. Team overview You'll join the Sky Q engineering organisation within Global Product Experience Engineering - the teams who build, test and run the platforms behind one of Sky's flagship products. Our automation squad works at the heart of delivery: Building and evolving the automation frameworks and pipelines used by multiple cross functional teams. Enabling fast, safe releases to production environments. Partnering with squads across Sky Q to embed automation thinking from the start of each initiative. The rewards There's a reason people love working here. As well as a competitive salary, you'll enjoy a wide ranging benefits package, plus the chance to work with cutting e dge tech on products used by millions. From development opportunities and community groups, through to discounts and wellbeing support - we'll give you the tools and environment to do the best work of your career. Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate . Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space: Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salo We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. We're tinkers, coders, and problem solvers . And we make it happen. Better products. Smarter platforms. And better ways of working. Working in Tech at Sky means building what's next - from automation platforms that keep Sky Q reliable, to tools that help engineers ship safely at scale. We're looking for a Senior Automation Engineer to help us evolve our Python based automation frameworks, CI/CD pipelines and tooling that power the Sky Q experience. You'll use your engineering craft to remove friction, increase quality, and enable teams to deliver features to millions of customers with confidence. What you'll do Design, build and maintain Python-based automation frameworks and tools that support end-to-end testing and operational workflows for Sky Q services. Develop, extend and optimise CI/CD pipelines (primarily in Jenkins) to ensure fast, reliable and repeatable delivery of software into multiple environments. Work hands on in Linux environments , scripting, configuring and troubleshooting automation jobs, agents and infrastructure to keep pipelines healthy and scalable. Collaborate with product engineering teams maintaining our Django and React applications , embedding automation into their workflows and improving observability and reliability. Introduce and integrate new tooling - including AI assisted development and test tools - to improve developer productivity, coverage and feedback cycles. Champion engineering best practices across the squad: code reviews, pair programming, clean code, robust testing strategies and continuous improvement. Act as a technical go to for automation , mentoring other engineers and helping shape the roadmap for our automation and test platforms. What you'll bring Advanced Python engineering capability - deep, hand s - on experience designing, building and maintaining robust automation frameworks using clean, modular, well tested code. High proficiency with CI/CD (Jenkins, Pipelines, CasC ) - able to architect, optimise, and troubleshoot complex pipelines, agents and integrations in large scale delivery environments. Strong Linux / VM operational expertise - confident working across distributed systems, debugging services, managing environments, and resolving complex infrastructure issues. Experience supporting or building web-based systems (e.g. Django backends and React frontends) and integrating them into automated pipelines. Solid competency in database operational support - capable of maintaining database related workflows, debugging data issues and supporting services used within automated pipelines. Competent API development experience - able to develop or extend backend APIs (e.g., Django/DRF) and integrate them seamlessly into automated workflows. Good awareness and some practical experience with AI a ssisted engineering workflows - such as using LLMs for automation tasks, applying ML assisted testing techniques, or experimenting with MCP style tooling to enhance productivity. Experience working effectively within Agile delivery teams - contributing to cross functional collaboration, communicating clearly, and supporting shared outcomes. An inclination toward continuous improvement - proactively seeking better ways of working, improving reliability, and helping raise engineering standards across the team. Team overview You'll join the Sky Q engineering organisation within Global Product Experience Engineering - the teams who build, test and run the platforms behind one of Sky's flagship products. Our automation squad works at the heart of delivery: Building and evolving the automation frameworks and pipelines used by multiple cross functional teams. Enabling fast, safe releases to production environments. Partnering with squads across Sky Q to embed automation thinking from the start of each initiative. The rewards There's a reason people love working here. As well as a competitive salary, you'll enjoy a wide ranging benefits package, plus the chance to work with cutting e dge tech on products used by millions. From development opportunities and community groups, through to discounts and wellbeing support - we'll give you the tools and environment to do the best work of your career. Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate . Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space: Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salo We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Senior Golang Developer - Kubernetes - Financial Services Excellent opportunity opens for an experienced Developer strong on Golang with experience in AWS and Kubernetes to join a highly regarded Financial Services entity's London office. You will act as the team lead and play a key role in building mission-critical financial applications that power trading, investment, and risk management systems across the firm. If you are passionate about working in a dynamic, fast-paced environment and are eager to apply your technical expertise to the financial services industry, this is the role for you. Key Responsibilities: Design, develop, and maintain high-performance Back End services using GoLang to support financial applications and services , including trading platforms, investment systems, and risk management tools. Build and deploy cloud-based solutions using Amazon Web Services (AWS), including services such as EC2, S3, RDS, DynamoDB, and Lambda to create scalable, reliable, and secure infrastructure. Implement and manage containerized applications using Kubernetes, ensuring seamless orchestration, scaling, and resilience in a cloud environment. Write clean, efficient, and well-documented code while following best practices for financial systems development, focusing on performance and security. Collaborate with other development teams, business analysts, and stakeholders to define and refine requirements, and ensure that applications meet financial regulatory standards and business needs. Optimize the performance of Back End services, ensuring low-latency responses and high availability, critical for financial services. Implement CI/CD pipelines, automated testing, and monitoring systems to ensure the reliability and stability of production systems. Proactively identify issues and bottlenecks in existing systems and propose solutions to improve the system's performance and scalability. Stay updated with new tools, technologies, and industry trends in cloud computing, containerization, and financial systems to continuously improve development practices and outcomes. Ideal Skills: Proven experience (2+ years) in GoLang Back End development, with a strong focus on performance optimization and building scalable systems for high-volume, high-frequency financial applications. Strong experience working with Amazon Web Services (AWS), including EC2, S3, RDS, DynamoDB, Lambda, and other cloud-native technologies. Hands-on experience with Kubernetes for deploying, managing, and scaling containerized applications in a cloud environment. Solid understanding of financial systems and services, particularly in areas such as trading platforms, investment management, and risk analytics. Experience in building microservices architectures and working with APIs (RESTful, gRPC, etc.) to integrate various systems. Strong knowledge of containerization (Docker) and continuous integration/deployment (CI/CD) practices. Experience with database systems (relational and NoSQL) and working with financial data. Familiarity with DevOps practices and tools to streamline the development life cycle, such as infrastructure-as-code (eg, Terraform or CloudFormation). Ability to troubleshoot and resolve issues in production environments, ensuring uptime and performance in high-pressure, mission-critical scenarios. Excellent communication skills to collaborate effectively with cross-functional teams and stakeholders in a fast-paced financial environment. Experience with serverless computing (AWS Lambda, etc.) to create efficient and scalable solutions. Knowledge of financial industry regulations and standards, particularly around data security and privacy. Familiarity with event-driven architectures or message queues (eg, Kafka, RabbitMQ) for Real Time data processing. Experience with automated testing frameworks and continuous delivery tools like Jenkins, GitLab CI, or CircleCI. Understanding of performance monitoring and observability tools such as CloudWatch, Prometheus, or Datadog. Interested? Please Apply! Golang Go AWS Kubernetes Terraform Bank Banking Finance Financial Services Crypto Blockchain Web3 Trading Exchange Digital Assets Hybrid Flexible Developer Software Engineer Backend Developer Golang Engineer Kafka Apache Kafka RabbitMQ AWS Lambda Cloud Platform
Mar 03, 2026
Full time
Senior Golang Developer - Kubernetes - Financial Services Excellent opportunity opens for an experienced Developer strong on Golang with experience in AWS and Kubernetes to join a highly regarded Financial Services entity's London office. You will act as the team lead and play a key role in building mission-critical financial applications that power trading, investment, and risk management systems across the firm. If you are passionate about working in a dynamic, fast-paced environment and are eager to apply your technical expertise to the financial services industry, this is the role for you. Key Responsibilities: Design, develop, and maintain high-performance Back End services using GoLang to support financial applications and services , including trading platforms, investment systems, and risk management tools. Build and deploy cloud-based solutions using Amazon Web Services (AWS), including services such as EC2, S3, RDS, DynamoDB, and Lambda to create scalable, reliable, and secure infrastructure. Implement and manage containerized applications using Kubernetes, ensuring seamless orchestration, scaling, and resilience in a cloud environment. Write clean, efficient, and well-documented code while following best practices for financial systems development, focusing on performance and security. Collaborate with other development teams, business analysts, and stakeholders to define and refine requirements, and ensure that applications meet financial regulatory standards and business needs. Optimize the performance of Back End services, ensuring low-latency responses and high availability, critical for financial services. Implement CI/CD pipelines, automated testing, and monitoring systems to ensure the reliability and stability of production systems. Proactively identify issues and bottlenecks in existing systems and propose solutions to improve the system's performance and scalability. Stay updated with new tools, technologies, and industry trends in cloud computing, containerization, and financial systems to continuously improve development practices and outcomes. Ideal Skills: Proven experience (2+ years) in GoLang Back End development, with a strong focus on performance optimization and building scalable systems for high-volume, high-frequency financial applications. Strong experience working with Amazon Web Services (AWS), including EC2, S3, RDS, DynamoDB, Lambda, and other cloud-native technologies. Hands-on experience with Kubernetes for deploying, managing, and scaling containerized applications in a cloud environment. Solid understanding of financial systems and services, particularly in areas such as trading platforms, investment management, and risk analytics. Experience in building microservices architectures and working with APIs (RESTful, gRPC, etc.) to integrate various systems. Strong knowledge of containerization (Docker) and continuous integration/deployment (CI/CD) practices. Experience with database systems (relational and NoSQL) and working with financial data. Familiarity with DevOps practices and tools to streamline the development life cycle, such as infrastructure-as-code (eg, Terraform or CloudFormation). Ability to troubleshoot and resolve issues in production environments, ensuring uptime and performance in high-pressure, mission-critical scenarios. Excellent communication skills to collaborate effectively with cross-functional teams and stakeholders in a fast-paced financial environment. Experience with serverless computing (AWS Lambda, etc.) to create efficient and scalable solutions. Knowledge of financial industry regulations and standards, particularly around data security and privacy. Familiarity with event-driven architectures or message queues (eg, Kafka, RabbitMQ) for Real Time data processing. Experience with automated testing frameworks and continuous delivery tools like Jenkins, GitLab CI, or CircleCI. Understanding of performance monitoring and observability tools such as CloudWatch, Prometheus, or Datadog. Interested? Please Apply! Golang Go AWS Kubernetes Terraform Bank Banking Finance Financial Services Crypto Blockchain Web3 Trading Exchange Digital Assets Hybrid Flexible Developer Software Engineer Backend Developer Golang Engineer Kafka Apache Kafka RabbitMQ AWS Lambda Cloud Platform
Career Choices Dewis Gyrfa Ltd
Birmingham, Staffordshire
£62,103 to £81,674 per year, (including allowances) London £65,826?to £81,674, National £62,103?to £78,054. Salary is dependent on location and technical skills as assessed at interview. Contract Type: Permanent Hours: Full time Disability Confident: Yes Closing Date: 19/03/2026 About this job If you would like to find out more about the role, the Platform Engineering team and what it's like to work at DBT, we are holding a Hiring Manager Q&A session for this role where you can virtually 'meet the team' on Wednesday 25th February. Please click here to book your spot. The Department for Business and Trade (DBT) has a clear mission to grow the economy. Our role is to help businesses invest, grow and export to create jobs and opportunities right across the country. We do this in three ways. Firstly, we help to build a strong, competitive business environment, where consumers are protected and companies rewarded for treating their employees properly. Secondly, we open international markets and ensure resilient supply chains. This can be through Free Trade Agreements, trade facilitation and multilateral agreements. Finally, we work in partnership with businesses every day, providing advance, finance and deal-making support to those looking to start up, invest, export and grow. The Digital, Data and Technology (DDaT) directorate develops and operates tools and services to support us in this mission. As Platform Test Lead, you will play a critical role in ensuring the DBT Platform is robust, secure, and scalable by embedding quality assurance into its design and delivery. You'll lead the development of platform-wide test strategies, support automated testing across infrastructure and services, and collaborate with technical leaders to drive continuous improvement. This role supports DBT's digital transformation goals and contributes to the strategic evolution of the platform. This is a technical and strategically critical role within our Technology portfolio at DBT, overseeing a platform that supports internal and external services. You will lead the evolution of the DBT Platform's testing strategy, ensuring it is robust, secure, scalable and efficient. You will work closely with platform engineers, technical architects, cyber security and service teams to embed quality assurance into the platform's design and delivery. You will play a key role in shaping how we test and assure platform capabilities, bringing your experience of test automation, infrastructure testing and DevOps practices. You'll work across DDaT to understand future needs and help teams validate and deliver against them. You'll also contribute to platform governance and technical decision-making, ensuring testing supports strategic goals. This is a technical leadership role requiring experience with cloud-hosted platforms. The successful candidate will be well-versed in implementing and optimising automated testing, deployment pipelines, and performance metrics like DORA. You will have an understanding of emerging technologies, enabling you to guide innovation and resilience across the platform. You must have a proven track record of leading test engineering for large-scale platform operations or infrastructure products, ensuring stability, scalability and strategic alignment with organisational goals. Main responsibilities Lead the design, implementation, and continuous improvement of automated test frameworks for platform components and services. Define and own platform-level test strategies, including integration, performance, security, and end-to-end testing across multi-account environments. Collaborate with Platform Engineers, Technical Architects, and Cyber SMEs to ensure testing supports platform priorities. Drive improvements in deployment testing, enabling faster, more reliable releases with reduced support burden. Support FinOps and observability initiatives by ensuring test coverage includes cost-impacting behaviours and performance metrics. Champion testability in platform design, simplifying environment setup and enabling self-service testing for service teams. Coach and mentor engineers in test automation, quality assurance, and continuous delivery practices. Monitor test suite health, reduce technical debt, and ensure test infrastructure is scalable and cost-effective. Proud member of the Disability Confident employer scheme
Mar 03, 2026
Full time
£62,103 to £81,674 per year, (including allowances) London £65,826?to £81,674, National £62,103?to £78,054. Salary is dependent on location and technical skills as assessed at interview. Contract Type: Permanent Hours: Full time Disability Confident: Yes Closing Date: 19/03/2026 About this job If you would like to find out more about the role, the Platform Engineering team and what it's like to work at DBT, we are holding a Hiring Manager Q&A session for this role where you can virtually 'meet the team' on Wednesday 25th February. Please click here to book your spot. The Department for Business and Trade (DBT) has a clear mission to grow the economy. Our role is to help businesses invest, grow and export to create jobs and opportunities right across the country. We do this in three ways. Firstly, we help to build a strong, competitive business environment, where consumers are protected and companies rewarded for treating their employees properly. Secondly, we open international markets and ensure resilient supply chains. This can be through Free Trade Agreements, trade facilitation and multilateral agreements. Finally, we work in partnership with businesses every day, providing advance, finance and deal-making support to those looking to start up, invest, export and grow. The Digital, Data and Technology (DDaT) directorate develops and operates tools and services to support us in this mission. As Platform Test Lead, you will play a critical role in ensuring the DBT Platform is robust, secure, and scalable by embedding quality assurance into its design and delivery. You'll lead the development of platform-wide test strategies, support automated testing across infrastructure and services, and collaborate with technical leaders to drive continuous improvement. This role supports DBT's digital transformation goals and contributes to the strategic evolution of the platform. This is a technical and strategically critical role within our Technology portfolio at DBT, overseeing a platform that supports internal and external services. You will lead the evolution of the DBT Platform's testing strategy, ensuring it is robust, secure, scalable and efficient. You will work closely with platform engineers, technical architects, cyber security and service teams to embed quality assurance into the platform's design and delivery. You will play a key role in shaping how we test and assure platform capabilities, bringing your experience of test automation, infrastructure testing and DevOps practices. You'll work across DDaT to understand future needs and help teams validate and deliver against them. You'll also contribute to platform governance and technical decision-making, ensuring testing supports strategic goals. This is a technical leadership role requiring experience with cloud-hosted platforms. The successful candidate will be well-versed in implementing and optimising automated testing, deployment pipelines, and performance metrics like DORA. You will have an understanding of emerging technologies, enabling you to guide innovation and resilience across the platform. You must have a proven track record of leading test engineering for large-scale platform operations or infrastructure products, ensuring stability, scalability and strategic alignment with organisational goals. Main responsibilities Lead the design, implementation, and continuous improvement of automated test frameworks for platform components and services. Define and own platform-level test strategies, including integration, performance, security, and end-to-end testing across multi-account environments. Collaborate with Platform Engineers, Technical Architects, and Cyber SMEs to ensure testing supports platform priorities. Drive improvements in deployment testing, enabling faster, more reliable releases with reduced support burden. Support FinOps and observability initiatives by ensuring test coverage includes cost-impacting behaviours and performance metrics. Champion testability in platform design, simplifying environment setup and enabling self-service testing for service teams. Coach and mentor engineers in test automation, quality assurance, and continuous delivery practices. Monitor test suite health, reduce technical debt, and ensure test infrastructure is scalable and cost-effective. Proud member of the Disability Confident employer scheme
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
Mar 03, 2026
Full time
We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem-solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards There's one thing people can't stop talking about when it comes to : the perks. Here's a taster: Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. We'd love to hear from you Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet. If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.
