Machine Learning Engineer

New Yesterday

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 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)

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)

TPBN1_UKTJ
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Location:
Crawley
Salary:
£100,000
Job Type:
FullTime
Category:
IT

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