Machine Learning Engineer An AI-driven start-up, backed by $20M in Series A funding, is looking for its first Machine Learning Engineer to help scale their product and infrastructure. The platform transforms educational content into smart, personalised learning tools - and is already seeing rapid user growth and strong traction in the market. This is a unique opportunity to join early, influence the technical roadmap, and work directly with experienced founders and a senior engineering team. What you'll be doing: Designing, building and deploying ML-powered features across a production platform Working across Python and TypeScript, integrating models into scalable, real-time systems Fine-tuning and training NLP models using techniques like transformers Driving the machine learning strategy and building best practices from the ground up Collaborating closely with product, engineering, and leadership What we're looking for: Strong commercial experience building and deploying ML models in production Proficiency in Python and familiarity with TypeScript/JavaScript Experience with NLP or recommendation systems is a bonus Excited by start-ups: product-minded, hands-on, and motivated by impact What's on offer: £100,000 - £120,000 salary + meaningful equity 4 days/week in a modern London office near Liverpool St Greenfield ML ownership with direct access to founding team A chance to shape the future of an AI product already loved by users
Jun 11, 2026
Full time
Machine Learning Engineer An AI-driven start-up, backed by $20M in Series A funding, is looking for its first Machine Learning Engineer to help scale their product and infrastructure. The platform transforms educational content into smart, personalised learning tools - and is already seeing rapid user growth and strong traction in the market. This is a unique opportunity to join early, influence the technical roadmap, and work directly with experienced founders and a senior engineering team. What you'll be doing: Designing, building and deploying ML-powered features across a production platform Working across Python and TypeScript, integrating models into scalable, real-time systems Fine-tuning and training NLP models using techniques like transformers Driving the machine learning strategy and building best practices from the ground up Collaborating closely with product, engineering, and leadership What we're looking for: Strong commercial experience building and deploying ML models in production Proficiency in Python and familiarity with TypeScript/JavaScript Experience with NLP or recommendation systems is a bonus Excited by start-ups: product-minded, hands-on, and motivated by impact What's on offer: £100,000 - £120,000 salary + meaningful equity 4 days/week in a modern London office near Liverpool St Greenfield ML ownership with direct access to founding team A chance to shape the future of an AI product already loved by users
Senior Data Scientist (Growth / GTM / Analytics) - Global Software Business - London Rate: £407 per day (Inside of IR35) Duration: 12 months Overview We are looking for a commercially minded Senior Data Scientist to drive data-led growth across a global, subscription-based business. This role focuses on identifying untapped market opportunities, improving customer targeting, and enabling data-driven go-to-market strategies. You'll work at the intersection of Data Science, Sales, Marketing, and Strategy, translating complex data into actionable insights that directly impact revenue growth. Key Responsibilities Market Opportunity & Revenue Modelling Develop models to quantify market opportunity (e.g. TAM/SAM) and identify whitespace across global segments Analyse customer and market data to uncover untapped revenue potential Deliver insights to support strategic planning and growth initiatives Customer & Growth Analytics Build and deploy propensity models to improve acquisition, upsell, and retention Develop customer segmentation frameworks to enhance targeting and campaign effectiveness Partner with commercial teams to optimise go-to-market strategies and sales performance Data Science & Modelling Design, develop, and iterate on predictive models that drive measurable business impact Apply statistical and machine learning techniques to large, complex datasets Ensure models are scalable, interpretable, and aligned with business needs Data Collaboration & Enablement Work closely with Data Engineering teams to productionise models and analytics workflows Leverage internal and external datasets to build rich customer intelligence Contribute to best practices in data quality, governance, and model monitoring Stakeholder Engagement Translate complex analyses into clear, actionable insights for senior stakeholders Present recommendations to influence commercial strategy, pricing, and product decisions Act as a trusted partner across technical and business teams Skills & Experience Strong experience in data science or advanced analytics roles (typically 5+ years) Advanced SQL skills with experience working on large-scale datasets (e.g. Databricks, Snowflake, BigQuery) Proficiency in Python for data analysis, modelling, and experimentation Experience building predictive models (e.g. propensity modelling, segmentation, forecasting) Demonstrated ability to deliver data-driven solutions that impact revenue or growth Strong communication skills with the ability to influence non-technical stakeholders Experience working cross-functionally with Sales, Marketing, Product, or Strategy teams Nice to Have Experience in SaaS, subscription-based, or platform businesses Exposure to pricing strategy, go-to-market planning, or commercial analytics Familiarity with market sizing methodologies Experience integrating third-party datasets What We're Looking For A commercially focused data scientist who prioritises business impact Someone comfortable working in ambiguous, fast-paced environments A strong communicator who can bridge data, technology, and business strategy Why Join High-impact role with direct influence on revenue growth and strategic decisions Opportunity to work on complex, global data challenges Collaborative environment across data, product, and commercial teams Please do send across an up to date CV to Rates depend on experience and client requirements
Jun 11, 2026
Contractor
Senior Data Scientist (Growth / GTM / Analytics) - Global Software Business - London Rate: £407 per day (Inside of IR35) Duration: 12 months Overview We are looking for a commercially minded Senior Data Scientist to drive data-led growth across a global, subscription-based business. This role focuses on identifying untapped market opportunities, improving customer targeting, and enabling data-driven go-to-market strategies. You'll work at the intersection of Data Science, Sales, Marketing, and Strategy, translating complex data into actionable insights that directly impact revenue growth. Key Responsibilities Market Opportunity & Revenue Modelling Develop models to quantify market opportunity (e.g. TAM/SAM) and identify whitespace across global segments Analyse customer and market data to uncover untapped revenue potential Deliver insights to support strategic planning and growth initiatives Customer & Growth Analytics Build and deploy propensity models to improve acquisition, upsell, and retention Develop customer segmentation frameworks to enhance targeting and campaign effectiveness Partner with commercial teams to optimise go-to-market strategies and sales performance Data Science & Modelling Design, develop, and iterate on predictive models that drive measurable business impact Apply statistical and machine learning techniques to large, complex datasets Ensure models are scalable, interpretable, and aligned with business needs Data Collaboration & Enablement Work closely with Data Engineering teams to productionise models and analytics workflows Leverage internal and external datasets to build rich customer intelligence Contribute to best practices in data quality, governance, and model monitoring Stakeholder Engagement Translate complex analyses into clear, actionable insights for senior stakeholders Present recommendations to influence commercial strategy, pricing, and product decisions Act as a trusted partner across technical and business teams Skills & Experience Strong experience in data science or advanced analytics roles (typically 5+ years) Advanced SQL skills with experience working on large-scale datasets (e.g. Databricks, Snowflake, BigQuery) Proficiency in Python for data analysis, modelling, and experimentation Experience building predictive models (e.g. propensity modelling, segmentation, forecasting) Demonstrated ability to deliver data-driven solutions that impact revenue or growth Strong communication skills with the ability to influence non-technical stakeholders Experience working cross-functionally with Sales, Marketing, Product, or Strategy teams Nice to Have Experience in SaaS, subscription-based, or platform businesses Exposure to pricing strategy, go-to-market planning, or commercial analytics Familiarity with market sizing methodologies Experience integrating third-party datasets What We're Looking For A commercially focused data scientist who prioritises business impact Someone comfortable working in ambiguous, fast-paced environments A strong communicator who can bridge data, technology, and business strategy Why Join High-impact role with direct influence on revenue growth and strategic decisions Opportunity to work on complex, global data challenges Collaborative environment across data, product, and commercial teams Please do send across an up to date CV to Rates depend on experience and client requirements
Lead Data Scientist - Manchester My client is seeking a Lead Data Scientist to own and drive the end-to-end data science strategy across high-impact business domains (e.g., risk, fraud, affordability, customer value). This role will translate complex, real-world financial data into production-grade machine learning systems that deliver measurable commercial and customer outcomes. The successful candidate will lead model development from ideation through deployment and monitoring, working closely with Data Engineers, Analysts, Product, Risk, and Technology stakeholders. They will set standards for experimentation, governance, and MLOps while mentoring and developing other data scientists within the function. This is a hands-on technical leadership role - both strategic and delivery-focused. The Role Strategic & Technical Leadership Define and evolve the data science roadmap aligned to business priorities. Identify high-value ML use cases and translate commercial problems into scalable analytical solutions. Lead end-to-end model lifecycle delivery: problem framing, feature engineering, experimentation, validation, deployment, monitoring, and iteration. Establish best practices for experimentation, evaluation, reproducibility, and documentation. Set standards for model governance, explainability, monitoring, and auditability within a regulated financial environment. Machine Learning & Delivery Architect and develop robust ML models (e.g., classification, regression, anomaly detection) using Python and cloud-based tooling. Design scalable feature pipelines in collaboration with Data Engineering. Lead productionisation efforts, including pipeline design, model versioning, and monitoring frameworks. Implement safe deployment strategies (e.g., champion/challenger models, shadow runs, A/B testing). Ensure model performance, drift detection, and continuous improvement processes are embedded. Stakeholder Engagement Partner with Risk, Compliance, Product, and Technology teams to ensure solutions are commercially viable and regulator-ready. Communicate complex modelling approaches and outcomes clearly to senior stakeholders and non-technical audiences. Influence strategic decision-making through insight and evidence-based recommendations. Governance & Risk • Own model documentation (model cards, lineage, assumptions, validation evidence).• Embed privacy-by-design, fairness, and bias monitoring practices.• Operate confidently within FCA-regulated environments and support audit and regulatory requirements. Team Leadership • Mentor and coach junior and mid-level data scientists.• Lead code reviews and promote engineering best practice (Git, testing, CI/CD awareness).• Contribute to hiring, technical assessment, and capability development.• Foster a culture of curiosity, collaboration, and high performance. About the Candidate The ideal candidate is commercially minded, technically strong, and delivery-focused. They understand that high-quality models create value only when deployed safely and embedded into business processes. They will be comfortable owning ambiguity, setting direction, and raising technical standards. They will combine statistical rigour with pragmatic decision-making and be confident influencing senior stakeholders. They will enjoy mentoring others and developing team capability alongside delivering impactful work. What My Client Is Looking For: • Significant hands-on experience building and deploying machine learning models into production environments.• Strong Python expertise (e.g., pandas, scikit-learn, ML frameworks) with production-quality coding standards.• Advanced SQL skills and deep understanding of relational data.• Strong statistical foundations and model validation expertise.• Experience working within cloud-based data platforms (AWS or equivalent).• Demonstrable experience productionising models and implementing monitoring frameworks.• Experience operating within a regulated environment (financial services preferred).• Ability to communicate effectively with senior stakeholders.• Experience mentoring or leading other data scientists. Desirable • Experience in credit risk, fraud detection, affordability modelling, or payments analytics.• Familiarity with model risk management frameworks.• Exposure to MLOps tooling (CI/CD pipelines, automated testing, model registries).• Experience with model explainability techniques (e.g., SHAP, LIME).• Experience shaping data science roadmaps or leading multiple concurrent initiatives. Benefits Hybrid working Training and development budget Flexible working Interested? Please Click Apply Now! Lead Data Scientist - Manchester
Jun 11, 2026
Full time
Lead Data Scientist - Manchester My client is seeking a Lead Data Scientist to own and drive the end-to-end data science strategy across high-impact business domains (e.g., risk, fraud, affordability, customer value). This role will translate complex, real-world financial data into production-grade machine learning systems that deliver measurable commercial and customer outcomes. The successful candidate will lead model development from ideation through deployment and monitoring, working closely with Data Engineers, Analysts, Product, Risk, and Technology stakeholders. They will set standards for experimentation, governance, and MLOps while mentoring and developing other data scientists within the function. This is a hands-on technical leadership role - both strategic and delivery-focused. The Role Strategic & Technical Leadership Define and evolve the data science roadmap aligned to business priorities. Identify high-value ML use cases and translate commercial problems into scalable analytical solutions. Lead end-to-end model lifecycle delivery: problem framing, feature engineering, experimentation, validation, deployment, monitoring, and iteration. Establish best practices for experimentation, evaluation, reproducibility, and documentation. Set standards for model governance, explainability, monitoring, and auditability within a regulated financial environment. Machine Learning & Delivery Architect and develop robust ML models (e.g., classification, regression, anomaly detection) using Python and cloud-based tooling. Design scalable feature pipelines in collaboration with Data Engineering. Lead productionisation efforts, including pipeline design, model versioning, and monitoring frameworks. Implement safe deployment strategies (e.g., champion/challenger models, shadow runs, A/B testing). Ensure model performance, drift detection, and continuous improvement processes are embedded. Stakeholder Engagement Partner with Risk, Compliance, Product, and Technology teams to ensure solutions are commercially viable and regulator-ready. Communicate complex modelling approaches and outcomes clearly to senior stakeholders and non-technical audiences. Influence strategic decision-making through insight and evidence-based recommendations. Governance & Risk • Own model documentation (model cards, lineage, assumptions, validation evidence).• Embed privacy-by-design, fairness, and bias monitoring practices.• Operate confidently within FCA-regulated environments and support audit and regulatory requirements. Team Leadership • Mentor and coach junior and mid-level data scientists.• Lead code reviews and promote engineering best practice (Git, testing, CI/CD awareness).• Contribute to hiring, technical assessment, and capability development.• Foster a culture of curiosity, collaboration, and high performance. About the Candidate The ideal candidate is commercially minded, technically strong, and delivery-focused. They understand that high-quality models create value only when deployed safely and embedded into business processes. They will be comfortable owning ambiguity, setting direction, and raising technical standards. They will combine statistical rigour with pragmatic decision-making and be confident influencing senior stakeholders. They will enjoy mentoring others and developing team capability alongside delivering impactful work. What My Client Is Looking For: • Significant hands-on experience building and deploying machine learning models into production environments.• Strong Python expertise (e.g., pandas, scikit-learn, ML frameworks) with production-quality coding standards.• Advanced SQL skills and deep understanding of relational data.• Strong statistical foundations and model validation expertise.• Experience working within cloud-based data platforms (AWS or equivalent).• Demonstrable experience productionising models and implementing monitoring frameworks.• Experience operating within a regulated environment (financial services preferred).• Ability to communicate effectively with senior stakeholders.• Experience mentoring or leading other data scientists. Desirable • Experience in credit risk, fraud detection, affordability modelling, or payments analytics.• Familiarity with model risk management frameworks.• Exposure to MLOps tooling (CI/CD pipelines, automated testing, model registries).• Experience with model explainability techniques (e.g., SHAP, LIME).• Experience shaping data science roadmaps or leading multiple concurrent initiatives. Benefits Hybrid working Training and development budget Flexible working Interested? Please Click Apply Now! Lead Data Scientist - Manchester
Senior / Lead Machine Learning Engineer - Time-Series, Pricing, Customer Behaviour, Feature stores, MLOps London Hybrid £100,000 - £120,000 + Equity This is a genuinely interesting opportunity for someone who enjoys solving large-scale, real-world machine learning problems rather than purely experimental work. The team is building forecasting, recommendation, pricing, and AI-driven decision systems that operate across a huge global dataset, with models directly influencing commercial decisions at scale. The role is heavily focused on machine learning engineering, particularly around time-series forecasting, scalable ML systems, feature stores, and MLOps. There's also some exposure to generative AI and LLM-related work, but this is primarily a deeply technical ML engineering role rather than a pure GenAI position. What makes the opportunity stand out is the blend of scale, technical complexity, and visibility. You'd be joining a relatively small but high-calibre AI team with strong research and engineering backgrounds, helping shape systems that directly influence pricing, marketing, and customer experience across thousands of businesses globally. They're looking for somebody who can stay hands-on technically while also helping guide more junior engineers and contribute to the wider technical direction of the team. The environment feels like a startup within a larger global business. There's plenty of ownership, freedom to influence technical decisions, and the opportunity to work on genuinely impactful AI systems at scale. The setup is hybrid with two days per week onsite in London. Experience around forecasting, time-series modelling, recommendation systems, production ML infrastructure, or large-scale MLOps environments would all be highly relevant. Salary: £100,000 - £120,000 plus equity and benefits. APPLY NOW for immediate consideration. N.B. - They do not offer visa sponsorship
Jun 11, 2026
Full time
Senior / Lead Machine Learning Engineer - Time-Series, Pricing, Customer Behaviour, Feature stores, MLOps London Hybrid £100,000 - £120,000 + Equity This is a genuinely interesting opportunity for someone who enjoys solving large-scale, real-world machine learning problems rather than purely experimental work. The team is building forecasting, recommendation, pricing, and AI-driven decision systems that operate across a huge global dataset, with models directly influencing commercial decisions at scale. The role is heavily focused on machine learning engineering, particularly around time-series forecasting, scalable ML systems, feature stores, and MLOps. There's also some exposure to generative AI and LLM-related work, but this is primarily a deeply technical ML engineering role rather than a pure GenAI position. What makes the opportunity stand out is the blend of scale, technical complexity, and visibility. You'd be joining a relatively small but high-calibre AI team with strong research and engineering backgrounds, helping shape systems that directly influence pricing, marketing, and customer experience across thousands of businesses globally. They're looking for somebody who can stay hands-on technically while also helping guide more junior engineers and contribute to the wider technical direction of the team. The environment feels like a startup within a larger global business. There's plenty of ownership, freedom to influence technical decisions, and the opportunity to work on genuinely impactful AI systems at scale. The setup is hybrid with two days per week onsite in London. Experience around forecasting, time-series modelling, recommendation systems, production ML infrastructure, or large-scale MLOps environments would all be highly relevant. Salary: £100,000 - £120,000 plus equity and benefits. APPLY NOW for immediate consideration. N.B. - They do not offer visa sponsorship
Principal AI Scientist - Learning & Assessment AI Location: UK Remote (Candidates must be UK based) Salary: 110,000 - 125,000 Employment Type: Permanent The Opportunity We're working with an innovative technology-led organisation that is transforming how AI is used within learning, assessment, and workforce skills development. They are seeking a Principal AI Scientist to lead the scientific design, validation, and evolution of next-generation AI-powered assessment and learning solutions embedded directly into the flow of work. This is a senior individual contributor role suited to someone with deep expertise across AI/ML, psychometrics, measurement science, and production-scale intelligent systems. The successful candidate will operate as a scientific authority within the organisation, shaping methodology, influencing product direction, and ensuring AI-driven solutions are fair, explainable, scalable, and scientifically rigorous. The role offers the opportunity to work at the intersection of modern AI systems, applied research, and enterprise-scale product delivery. The Role As Principal AI Scientist, you will take ownership of the scientific and methodological direction of AI-enabled learning and assessment products. You will work closely with product leadership, engineering teams, data scientists, and domain experts to translate advanced research into production-ready systems that deliver measurable user and business outcomes. This position requires someone comfortable operating in highly complex environments with significant technical, ethical, and commercial considerations. Key Responsibilities Scientific Leadership & Product Ownership Lead the scientific strategy for AI-enabled assessment, learning, and skills products Define robust methodologies balancing innovation, scalability, fairness, validity, and explainability Act as the senior scientific authority for assessment and measurement decisions Establish scientific standards, reusable frameworks, and evaluation methodologies Lead validation studies to ensure reliability, consistency, fairness, and performance stability Define and monitor scientific KPIs including drift detection, bias indicators, and model effectiveness Identify and mitigate scientific and measurement risks associated with AI systems at scale AI, Machine Learning & Modern AI Systems Apply AI and machine learning techniques, including LLMs and foundation models, to learning and assessment use cases Support development of AI-powered capabilities such as: Skills inference Adaptive assessment Automated content generation AI-driven feedback and reasoning systems Contribute to the evaluation and governance of agentic AI workflows Partner with engineering teams to ensure scientific integrity is maintained throughout implementation and deployment Support lifecycle monitoring and continuous improvement of production AI systems Research, Innovation & Strategic Influence Translate research findings into scalable, commercially viable product capabilities Produce thought leadership content including whitepapers and scientific insights Influence product and AI strategy through scientific expertise and evidence-based recommendations Support internal and external discussions around responsible AI and ethical AI implementation Engage with enterprise stakeholders and senior leadership on scientific and AI-related topics Required Experience Advanced degree (MSc or PhD preferred) in: Psychometrics Educational Measurement Statistics Machine Learning Artificial Intelligence Data Science Or equivalent commercial experience Proven experience building or leading AI-enabled assessment or measurement systems Deep expertise in validation methodologies, statistical modelling, and measurement theory Strong applied experience with machine learning and AI systems in production environments Practical understanding of modern AI architectures including Large Language Models (LLMs) Experience collaborating closely with engineering and product teams Ability to influence technical and strategic decisions through expertise rather than direct authority Experience operating in complex, high-ambiguity environments with significant business or ethical risk considerations Desirable Experience Experience applying LLMs within learning, workforce skills, or assessment products Exposure to adaptive testing, continuous assessment, or automated item/content generation Experience evaluating or governing AI agentic workflows Background within learning technology, education technology, workforce development, or skills ecosystems Experience working on enterprise-scale or long-lived AI platforms What They're Looking For A scientifically rigorous thinker with strong commercial awareness Someone passionate about responsible and explainable AI Comfortable balancing research innovation with practical delivery Strong communicator able to work across technical and non-technical audiences A collaborative leader who enjoys solving complex real-world problems Package 110,000 - 125,000 salary Fully remote role within the UK High-impact position within a cutting-edge AI environment Opportunity to influence next-generation AI products at scale Please note: Applicants must be based in the UK. Sponsorship is not available for this position.
Jun 05, 2026
Full time
Principal AI Scientist - Learning & Assessment AI Location: UK Remote (Candidates must be UK based) Salary: 110,000 - 125,000 Employment Type: Permanent The Opportunity We're working with an innovative technology-led organisation that is transforming how AI is used within learning, assessment, and workforce skills development. They are seeking a Principal AI Scientist to lead the scientific design, validation, and evolution of next-generation AI-powered assessment and learning solutions embedded directly into the flow of work. This is a senior individual contributor role suited to someone with deep expertise across AI/ML, psychometrics, measurement science, and production-scale intelligent systems. The successful candidate will operate as a scientific authority within the organisation, shaping methodology, influencing product direction, and ensuring AI-driven solutions are fair, explainable, scalable, and scientifically rigorous. The role offers the opportunity to work at the intersection of modern AI systems, applied research, and enterprise-scale product delivery. The Role As Principal AI Scientist, you will take ownership of the scientific and methodological direction of AI-enabled learning and assessment products. You will work closely with product leadership, engineering teams, data scientists, and domain experts to translate advanced research into production-ready systems that deliver measurable user and business outcomes. This position requires someone comfortable operating in highly complex environments with significant technical, ethical, and commercial considerations. Key Responsibilities Scientific Leadership & Product Ownership Lead the scientific strategy for AI-enabled assessment, learning, and skills products Define robust methodologies balancing innovation, scalability, fairness, validity, and explainability Act as the senior scientific authority for assessment and measurement decisions Establish scientific standards, reusable frameworks, and evaluation methodologies Lead validation studies to ensure reliability, consistency, fairness, and performance stability Define and monitor scientific KPIs including drift detection, bias indicators, and model effectiveness Identify and mitigate scientific and measurement risks associated with AI systems at scale AI, Machine Learning & Modern AI Systems Apply AI and machine learning techniques, including LLMs and foundation models, to learning and assessment use cases Support development of AI-powered capabilities such as: Skills inference Adaptive assessment Automated content generation AI-driven feedback and reasoning systems Contribute to the evaluation and governance of agentic AI workflows Partner with engineering teams to ensure scientific integrity is maintained throughout implementation and deployment Support lifecycle monitoring and continuous improvement of production AI systems Research, Innovation & Strategic Influence Translate research findings into scalable, commercially viable product capabilities Produce thought leadership content including whitepapers and scientific insights Influence product and AI strategy through scientific expertise and evidence-based recommendations Support internal and external discussions around responsible AI and ethical AI implementation Engage with enterprise stakeholders and senior leadership on scientific and AI-related topics Required Experience Advanced degree (MSc or PhD preferred) in: Psychometrics Educational Measurement Statistics Machine Learning Artificial Intelligence Data Science Or equivalent commercial experience Proven experience building or leading AI-enabled assessment or measurement systems Deep expertise in validation methodologies, statistical modelling, and measurement theory Strong applied experience with machine learning and AI systems in production environments Practical understanding of modern AI architectures including Large Language Models (LLMs) Experience collaborating closely with engineering and product teams Ability to influence technical and strategic decisions through expertise rather than direct authority Experience operating in complex, high-ambiguity environments with significant business or ethical risk considerations Desirable Experience Experience applying LLMs within learning, workforce skills, or assessment products Exposure to adaptive testing, continuous assessment, or automated item/content generation Experience evaluating or governing AI agentic workflows Background within learning technology, education technology, workforce development, or skills ecosystems Experience working on enterprise-scale or long-lived AI platforms What They're Looking For A scientifically rigorous thinker with strong commercial awareness Someone passionate about responsible and explainable AI Comfortable balancing research innovation with practical delivery Strong communicator able to work across technical and non-technical audiences A collaborative leader who enjoys solving complex real-world problems Package 110,000 - 125,000 salary Fully remote role within the UK High-impact position within a cutting-edge AI environment Opportunity to influence next-generation AI products at scale Please note: Applicants must be based in the UK. Sponsorship is not available for this position.
Director of AI Manchester (Office Based) Excellent Salary + Bonus + Benefits Are you a visionary AI leader ready to shape the future of enterprise AI; from strategic roadmap to hands-on implementation? Join a fast-scaling, international SaaS company that's transforming its industry through relentless innovation, advanced product development and investment in next-generation AI solutions. This is a rare, high-impact opportunity to define and drive the end-to-end AI agenda of a multi-award-winning business backed by a world-class leadership team. As Director of AI, you will own the company's AI vision - leading strategy development, technical execution, and operational scaling across Machine Learning, Generative AI, Large language Models and beyond. Your leadership will directly influence product innovation, operational excellence, and commercial success. Role Overview Define and drive the enterprise AI strategy - identifying opportunities for innovation, automation, and market differentiation using advanced AI/ML technologies. Own the full lifecycle of AI initiatives, from vision and roadmap to technical architecture, delivery, optimisation, and governance. Build and lead cross-functional AI teams, ensuring alignment between technical execution and strategic business goals. Evaluate emerging technologies (e.g. LLMs, RAG, vector search, knowledge graphs) and make evidence-based recommendations to stakeholders. Establish best practices for responsible AI development, including risk management, compliance, and explainability. Partner with senior leadership to integrate AI into core business functions and customer-facing products at speed and scale. What You Bring Proven leadership in delivering enterprise-scale AI strategies, ideally in a high-growth SaaS or technology-led environment. Strong academic or practical background in AI, ML, Data Science, Computer Science or a related STEM field. Demonstrated hands-on expertise in building and deploying advanced ML and Generative AI models in production (including RAG Architecture) Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD, MLOps, and DevSecOps. Experience building AI governance frameworks to address ethical risk, model accuracy, and regulatory compliance. Why Join? This is a career-defining opportunity to shape the AI strategy of a high-growth, global and entrepreneurial organisation. You'll work alongside a visionary leadership team and have the autonomy to innovate, influence, and scale AI solutions that have real-world commercial impact. Enjoy a highly competitive compensation package, including: Excellent base salary Generous performance-based bonus Private healthcare, pension scheme, and premium benefits A dynamic, innovation-first culture with real career progression DAI(phone number removed)AM INDAMS
Oct 02, 2025
Full time
Director of AI Manchester (Office Based) Excellent Salary + Bonus + Benefits Are you a visionary AI leader ready to shape the future of enterprise AI; from strategic roadmap to hands-on implementation? Join a fast-scaling, international SaaS company that's transforming its industry through relentless innovation, advanced product development and investment in next-generation AI solutions. This is a rare, high-impact opportunity to define and drive the end-to-end AI agenda of a multi-award-winning business backed by a world-class leadership team. As Director of AI, you will own the company's AI vision - leading strategy development, technical execution, and operational scaling across Machine Learning, Generative AI, Large language Models and beyond. Your leadership will directly influence product innovation, operational excellence, and commercial success. Role Overview Define and drive the enterprise AI strategy - identifying opportunities for innovation, automation, and market differentiation using advanced AI/ML technologies. Own the full lifecycle of AI initiatives, from vision and roadmap to technical architecture, delivery, optimisation, and governance. Build and lead cross-functional AI teams, ensuring alignment between technical execution and strategic business goals. Evaluate emerging technologies (e.g. LLMs, RAG, vector search, knowledge graphs) and make evidence-based recommendations to stakeholders. Establish best practices for responsible AI development, including risk management, compliance, and explainability. Partner with senior leadership to integrate AI into core business functions and customer-facing products at speed and scale. What You Bring Proven leadership in delivering enterprise-scale AI strategies, ideally in a high-growth SaaS or technology-led environment. Strong academic or practical background in AI, ML, Data Science, Computer Science or a related STEM field. Demonstrated hands-on expertise in building and deploying advanced ML and Generative AI models in production (including RAG Architecture) Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD, MLOps, and DevSecOps. Experience building AI governance frameworks to address ethical risk, model accuracy, and regulatory compliance. Why Join? This is a career-defining opportunity to shape the AI strategy of a high-growth, global and entrepreneurial organisation. You'll work alongside a visionary leadership team and have the autonomy to innovate, influence, and scale AI solutions that have real-world commercial impact. Enjoy a highly competitive compensation package, including: Excellent base salary Generous performance-based bonus Private healthcare, pension scheme, and premium benefits A dynamic, innovation-first culture with real career progression DAI(phone number removed)AM INDAMS
