Research Engineer / Scientist, Post-training & Reinforcement Learning - London

The Models team builds the foundational models that power our cutting-edge agentic technology. We focus on training techniques to optimize model capabilities specifically for agent applications. This allows us to achieve the best performance at a given inference cost.

Our work spans the development of Large Language Models (LLMs) and Vision-Language Models (VLMs), enabling agents to perceive, understand, and act within complex environments. We own the entire pipeline including synthetic data generation, environment design, mid-training, supervised fine-tuning, offline reinforcement learning, online reinforcement learning, reward modelling, transition modelling, etc. Our team also has dedicated MLOps, Infra and Inference support at scale.