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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - Agentic AI & Reinforcement Learning - **Company:** Viridien - **Location:** Crawley, UK - **Salary:** £55,432.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, Distributed Computing Environment, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Machine Learning, Language Modeling, Open Source Technology, Performance Tuning, Tensorflow, Workflow Management Systems, Reinforcement Learning, Supervised Learning, Pytorch, Large Language Models, Multi-Agent Systems, Generative AI, Information Technology, Virtual Agents - **Published:** August 18, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5846927452 ## About the Role * Degree in computer science, artificial intelligence, machine learning, engineering or a related discipline, or equivalent practical experience. * Strong Python programming and software-engineering skills. * Experience developing machine-learning, generative AI or LLM applications. * Practical experience with PyTorch, JAX, TensorFlow or a similar framework. * Understanding of agentic AI concepts such as tool calling, planning, memory and workflow orchestration. * Knowledge of reinforcement learning, preference optimisation or sequential decision-making. * Experience designing model evaluations and translating research ideas into reliable software. Desirable * Experience developing multi-agent systems using LangGraph, AutoGen, smolagents or similar frameworks. * Experience with LLM fine-tuning, DPO, GRPO, PPO, RLHF or RLAIF. * Experience designing reward functions, graders or agent training environments. * Experience with Model Context Protocol and tool integration. * Experience deploying open-source language or vision-language models, including distributed training or GPU computing. * Experience applying AI to scientific, engineering, energy or geoscience workflows. ## Description * Design and develop single-agent and multi-agent systems for complex workflows. * Build reasoning, planning, task decomposition, memory, tool-use and agent-collaboration capabilities. * Integrate LLMs, vision-language models, retrieval systems and domain-specific tools. * Fine-tune and adapt foundation models using supervised learning, preference optimisation and reinforcement learning where appropriate. * Develop training environments, reward functions, graders and feedback mechanisms. * Build evaluation, guardrail and monitoring approaches for agent reliability. * Convert prototypes into production-ready APIs, services and reusable software components., We are also dedicated to ensuring that our hiring process accessible to all. If you require any reasonable adjustments to fully participate in the application or interview stages, please don't hesitate to contact your recruiter directly. ## Related Videos - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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