Hybrid Senior Machine Learning Engineer

at BAE Systems Digital Intelligence

• Job title: Senior Machine Learning Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: No Education Requirement
• Tech skills: AWS, Python, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, London, United Kingdom

About the role

• Senior ML Engineer designing and developing machine learning models for national security. Collaborating with cross-functional teams to deliver scalable solutions in defense applications.

Responsibilities

• Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications
• Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements
• Transition validated experiments into production-ready solutions, working closely with other engineers on deployment and monitoring
• Build and optimise ML pipelines using AWS services and experiment tracking tools
• Develop and integrate LLM-powered solutions for tracing, evaluation, and production monitoring
• Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails
• Design feature engineering approaches and contribute to feature store development
• Support production models through monitoring, performance analysis, and continuous improvement
• Apply responsible AI practices, including model explainability and fairness assessment
• Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value
• Mentor junior colleagues and share learnings across the team.

Requirements

• Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow
• Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments
• Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation
• Proven track record transitioning models from experimentation to production with appropriate governance and quality controls
• Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control)
• Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures
• Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph
• Understanding of model evaluation, validation techniques, and production monitoring
• Experience working in cross-functional teams from problem framing through to production delivery
• Ability to communicate complex findings to non-technical audiences clearly
• Strong problem-solving skills and knowing when AI is not the answer.

Benefits

• Work-life balance is important; you can work around core hours with flexible and part-time working
• 25 days holiday a year and the option to buy/sell and carry over from the year before
• Our flexible benefits package includes private medical and dental insurance, a competitive pension scheme, cycle to work scheme, taste cards and more
• You’ll have a dedicated Career Manager to help you develop your career and guide you on your journey through BAE
• You’ll be part of our company bonus scheme
• You are welcome to join any/all of our Diversity and Support groups.