Machine Learning Engineer

Location: South East London

ML Engineer - Must hold active DV Clearance This is an exciting time to join a team to help pioneer both customer's and an AI adoption journey. Not only will you be directly making a huge impact through the solutions you develop, youll be doing it for an organisation who makes a huge impact to the security of the UK.

Core Duties 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 You will have experience in many of the following:
Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or Tensor Flow Strong experience with AWS ML services (Sage Maker, 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) It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them

Experience with advanced LLM techniques: agents, tool use, and agentic workflows

Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications

Experience with feature stores (Feast, AWS Feature Store)

Experience with containerisation (Docker) and orchestration (Kubernetes, ECS)