Senior Machine Learning Engineer
16 Days Old
Lead experimentation cycles: hypothesis, evaluation, iteration, and validation
Take successful ML approaches into production, including deployment and monitoring
Build and optimise ML pipelines on AWS
Develop LLM-powered solutions, including evaluation and observability
Apply strong MLOps practices: experiment tracking, versioning, and reproducibility
Communicate findings clearly to technical and non-technical stakeholders
Mentor junior engineers and contribute to team best practices
This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow)
Production experience with AWS ML services (e.g. SageMaker, Lambda, S3)
Proven ability to move models from experimentation into live systems
Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar)
Hands-on exposure to LLM / GenAI applications, including RAG
Nice to have: Experience with advanced LLM techniques (e.g. agents, tool use)
Familiarity with vector databases and feature stores
Experience with Docker, Kubernetes, or Infrastructure as Code
Important: Security clearance required (or eligibility to obtain it).
Benefits: Hybrid working with flexibility
25 days holiday plus buy/sell options
Competitive pension, bonus, and benefits
Strong career development and mentoring
Opportunity to work on mission-critical AI supporting UK security
Ok, Im in whats next? Please apply with your latest CV.
TPBN1_UKTJ
- Location:
- London
- Salary:
- £65,000
- Job Type:
- FullTime
- Category:
- IT;IT
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