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Research Engineer (Model Training)
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Research Engineer (Model Training)
Research Engineer (Model Training)
Physical AI Lab | London or Paris Compensation: Up to £220K + equity package
About the Role
This is a VC-backed physical AI lab building universal foundation models for general-purpose robots. The ambition is to automate the large, under-served parts of the economy that traditional industrial robotics hasn’t touched.
The team takes a vertical approach: simulation-first data generation, proprietary omni-models, tight hardware integration, and custom silicon. The team is small, deeply technical, and includes individuals behind some of the most significant advances in robotics and AI in recent years.
You’d be joining the team responsible for the core training stack — the infrastructure and methods behind the models that power real-world robotic systems.
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Responsibilities
- Train large-scale vision-language and multimodal foundation models across robotics tasks
- Build and run RL post-training pipelines — reward modelling, policy optimisation, and feedback-driven learning at scale
- Train foundation models used to synthesise high-quality simulation data
- Design systems for long-context video training, including sequence parallelism at scale
- Support autoregressive and diffusion-based approaches for actions, video, and control
- Own data flow, memory movement, and GPU utilisation across complex training loops
- Translate field performance and failure modes into new training signals and better models
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Requirements
- Extensive experience in large-scale distributed training and GPU performance tuning
- Direct experience in at least one of:
- RL post-training for large models
- Video generation / world model training
- Robotics-focused model training
- Strong background in ML infrastructure and/or high-performance computing
- Direct experience training large vision-language or multimodal foundation models
- Experience from a top AI lab, frontier model team, or elite infrastructure group
Shortlisted candidates will be contacted within 48 hours.
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