Machine learning engineer - agentic ai & reinforcement learning in Oxford

Viridien () is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights, innovations, and solutions that efficiently and responsibly resolve complex natural resource, digital, energy transition and infrastructure challenges. Are you interested in working on real world data like no other?Viridien is expanding its capabilities in agentic AI, large language models and reinforcement learning for complex scientific and enterprise workflows. We are looking for a hands-on Machine Learning Engineer to design, develop and evaluate intelligent agent systems, turning emerging AI methods into reliable, scalable and reusable solutions for truly real world data. About the Team Learn more about our work and the team on our website, recent blog post featuring one of our senior machine learning engineers and our latest Voices of Viridien. Key responsibilities 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. Experience and skills Required 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 Py Torch, JAX, Tensor Flow 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 Lang Graph, Auto Gen, 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. Why work with us?Competitive salary commensurate with experience Highly attractive bonus scheme Initial 22 days annual leave with future increases, complemented by a flexible buying and selling holiday program Hybrid working with two days at home, flexible working Company pension with generous employer contribution Wellbeing Unmind app – puts you in control of your mental health A flexible benefits platform with numerous discount schemes - gym membership, restaurants, cinema tickets, and much more!Cycle purchase scheme Flexible Private Medical & Dental care programmes