Senior ML Engineer for National Security AI & MLOps

BAE Systems; Greater London; Hybrid; GBP 120,000 - 150,000; Full time

Benefits offered by this job

Private medical and dental insurance

Pension scheme

Cycle to work scheme

Taste cards

Job summary

BAE Systems Digital Intelligence in London is seeking a Senior ML Engineer to design, optimize and productionize machine learning and GenAI solutions for national security problems. You will collaborate with Data Scientists, Software Engineers, Product Management and Government stakeholders across the full lifecycle from hypothesis through production deployment.

You will balance rapid experimentation with production-grade reliability, implement robust experiment tracking, and work with AWS-based

Qualifications

• 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 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.

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.

Skills

Python

scikit-learn

XGBoost

PyTorch

TensorFlow

SageMaker

Lambda

S3

MLflow

Weights & Biases

LLMOps

LangSmith

LangChain

LangGraph

RAG

Tools

SageMaker

Lambda

S3

Docker

Kubernetes

Terraform

CloudFormation

Job description

BAE Systems Digital Intelligence in London is seeking a Senior ML Engineer to design, optimize and productionize machine learning and GenAI solutions for national security problems. You will collaborate with Data Scientists, Software Engineers, Product Management and Government stakeholders across the full lifecycle from hypothesis through production deployment.

You will balance rapid experimentation with production-grade reliability, implement robust experiment tracking, and work with AWS-based