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Senior Machine Learning Engineer - Behavioural Modeling & Threat Detection - £150,000 - £180,000 - Fully Remote UK BASED CANDIDATES ONLY My client is looking for an experienced Machine Learning Engineer ready to play a pivotal role in shaping the technical direction of their behavioural modelling and threat detection systems. This position offers the opportunity to influence not just their engineering roadmap, but how they fundamentally approach solving complex, real-world security challenges with data. You'll work at the intersection of data science, ML infrastructure, and product innovation, leading efforts to build and evolve ML-driven capabilities, while also ensuring the reliability and scalability of their models in production environments. What You'll Do Spearhead the design and refinement of machine learning models focused on understanding behaviour patterns and identifying cybersecurity anomalies. Partner with product, engineering, and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams to operationalize models and ship ML-powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy with tactical improvements. Champion code quality, observability, and resilience within their ML systems through reviews and hands-on contributions. Help shape their internal ML standards and practices, ensuring they stay ahead of industry advancements. Offer technical mentorship and be a thought partner to colleagues across data, ML, and engineering disciplines. What We're Looking For Hands-on experience in developing and deploying machine learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially in cross-functional contexts. Bonus Experience (Nice to Have) Exposure to large language models (LLMs) or foundational model adaptation. Previous work in cybersecurity, anomaly detection, or behavioural analytics. Familiarity with orchestration frameworks (Airflow or similar). Experience with scalable ML systems, pipelines, or real-time data processing. Advanced degree or equivalent experience in ML/AI research or applied science. Cloud platform proficiency (AWS, GCP, Azure). If this sounds like something you would be interested in, please apply with your latest CV, a number to reach you on and I will be in touch. Alternatively, you can email me at . RSG Plc is acting as an Employment Agency in relation to this vacancy.