Machine Learning Engineer

Data Scientist / Machine Learning Scientist

Location: London (Hybrid)

Contract: Outside IR35

Rate: £500–£550 per day (depending on interview outcome)

We’re looking for AI operators who ship — not experiment.

This is an opportunity to join a major AI build focused on deploying real-world LLM and agentic systems at scale across both AI products and enterprise transformation initiatives.

You’ll be working in a production-first environment where the emphasis is on building reliable, scalable AI systems that deliver measurable business impact.

What You’ll Be Working On

• Designing and building AI agents and agentic workflows powered by LLMs
• Developing systems using RAG, reasoning, planning, memory, and tool orchestration
• Building multi-step intelligent systems capable of real-world tool usage
• Working with MCP-style architectures (or equivalent) to structure context and improve interoperability
• Contributing to recommendation, classification, and forecasting systems using large-scale datasets
• Automating business workflows and decision-making processes through AI-driven solutions

What You’ll Be Doing

• Owning projects end-to-end from concept through to production deployment and iteration
• Building and deploying AI agents that operate reliably in production environments
• Integrating AI systems into APIs, products, and operational workflows
• Collaborating closely with engineering teams to ensure scalability, observability, and maintainability
• Making pragmatic decisions balancing model performance, latency, and cost efficiency

Core Requirements

• Strong Python skills with experience writing production-grade code
• Proven experience deploying LLM-powered systems into production environments
• Hands-on experience with LangChain, LangGraph, or equivalent orchestration frameworks
• Experience building AI agents and agentic workflows with tool usage and multi-step reasoning
• Strong understanding and implementation experience of RAG systems
• Familiarity with MCP/FastMCP/FastAPI or similar orchestration patterns
• Strong understanding of LLM trade-offs including hallucination mitigation, latency, and cost optimisation
• Experience deploying AI systems in cloud environments such as AWS, GCP, or Azure
• Working knowledge of SQL/data manipulation (Working knowledge of SQL or data manipulation is expected, but it is not a primary focus for this role.)

Strong signals include:

• Experience working on SaaS or B2B AI products or delivering AI-driven transformation within an organisation.
• A background in high-growth or scaling environments, where speed and pragmatism are critical.
• Clear evidence of systems that are actively used and delivering value, rather than experimental work.

Ideal Background

• Masters degree or higher in Computer Science, Mathematics, Engineering, or a related technical field
• Experience building and iterating on AI systems delivering measurable value
• Strong ownership mindset and ability to operate in fast-moving environments
• Product-focused approach with a bias toward delivering impact

Why This Role

• Work on live AI systems used at scale
• Join a well-supported AI engineering environment
• High ownership and visibility across products and operations
• Opportunity to shape enterprise AI adoption in a meaningful way