Senior Machine Learning Engineer - GenAI, LLM, RAG

Senior Machine Learning Engineer - GenAI, LLM, RAG - 12 month contract

I'm looking for Machine Learning Engineers (and Senior Data Scientists with strong engineering capability) who have real, hands-on experience building GenAI applications end-to-end. Not just prototypes, but production systems.

This is a full-stack ML Engineering role where you'll design, build, deploy, and monitor GenAI applications that integrate LLMs as part of a wider system.

You'll be working on:

• Building production-grade GenAI applications using Python
• Developing LLM-powered systems with LangChain, LangSmith, and modern Python libraries
• Designing and implementing RAG pipelines, vector stores, and retrieval logic
• Building agentic workflows, tool-calling, and multi-step reasoning systems
• Implementing guardrails, safety layers, and controls
• Designing monitoring for latency, drift, hallucinations, cost, and safety signals
• Integrating LLMs into broader application architectures (APIs, services, orchestration)
• Working across the full life cycle: data prep - modelling - evaluation - deployment - observability

We're looking for people who have:

• Delivered real GenAI applications into production, not just PoCs
• Strong Python engineering skills
• Experience with LangChain, LangSmith, LlamaIndex, or similar frameworks
• Deep understanding of LLM behaviour, prompting, evaluation, and optimisation
• Experience building monitoring, logging, and guardrail frameworks
• Ability to work across the stack: data, model, application, and infrastructure
• Strong communication skills and ability to work with product, engineering, and business teams

This is ideal for ML Engineers who love building end-to-end systems, not just models. People who can take a GenAI idea from concept to production and own the full life cycle.

If you've built and shipped GenAI applications and want to work on high-impact, enterprise-scale projects, please apply.