Machine Learning Engineer – Agentic LLM Systems (Contract)
Posted Today by Experis UK
Negotiable
Outside
Remote
England, United Kingdom
Summary: The Machine Learning Engineer role focuses on designing and scaling agentic AI systems, specifically large language models (LLMs) that can perform tasks such as planning, reasoning, and executing code. The engineer will collaborate with researchers to enhance the reliability and functionality of these systems in production environments. Key responsibilities include developing tools and frameworks, debugging complex ML systems, and conducting experiments to optimize performance. This position requires significant experience in ML/AI and a strong background in Python programming.
Key Responsibilities:
- Design and build tools, workflows, and infrastructure for agentic LLM systems
- Work with researchers to diagnose and fix failures in agent-generated code
- Develop frameworks for tool-calling, multi-step planning, and orchestration
- Build and run experiments to improve reliability, latency, and success rates
Key Skills:
- 4+ years’ experience in ML/AI (LLMs, recommender systems, optimisation, or similar)
- Proven hands-on work with LLM agents / tool-using models / orchestrated workflows
- Strong Python with PyTorch or TensorFlow
- Comfortable debugging complex, distributed ML systems
- Experience running and analysing large-scale ML experiments
- Master’s (or PhD) in Computer Science, AI, ML, or related field
- Experience with LangChain, LangGraph, or similar orchestration frameworks (nice to have)
- Research track record (publications, Kaggle, or open-source) (nice to have)
- Backend experience (APIs) and some frontend (React/JavaScript) for internal tools (nice to have)
Salary (Rate): undetermined
City: undetermined
Country: United Kingdom
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Machine Learning Engineer – Agentic LLM Systems (Contract) We’re working with a leading tech organisation building agentic AI systems – LLMs that can plan, reason, call tools, and write/execute code. We’re hiring a Machine Learning Engineer to help design and scale these systems into production.
Role Overview: You’ll focus on making LLM agents reliable, scalable, and useful in real products. You will:
- Design and build tools, workflows, and infrastructure for agentic LLM systems
- Work with researchers to diagnose and fix failures in agent-generated code
- Develop frameworks for tool-calling, multi-step planning, and orchestration
- Build and run experiments to improve reliability, latency, and success rates
What We’re Looking For 4+ years’ experience in ML/AI (LLMs, recommender systems, optimisation, or similar) Proven hands-on work with LLM agents / tool-using models / orchestrated workflows Strong Python with PyTorch or TensorFlow Comfortable debugging complex, distributed ML systems Experience running and analysing large-scale ML experiments Master’s (or PhD) in Computer Science, AI, ML, or related field Nice to have: Experience with LangChain, LangGraph, or similar orchestration frameworks Research track record (publications, Kaggle, or open-source) Backend experience (APIs) and some frontend (React/JavaScript) for internal tools
Contract Details: Outside IR35 6–12 months (long-term extensions) Remote (UK-based candidates only) Please apply for immediate consideration.