Senior Robot Learning Engineer

Senior Robot Learning Engineer focuses on architect, train, and evaluate end-to-end large behaviour models for bi-manual and mobile manipulation.

What the role involves

• Architect, train, and evaluate end-to-end large behaviour models for bi-manual and mobile manipulation.
• Develop language conditioning for true multi-task generalisation.
• Advance diffusion transformer policies, mature VLA integration.
• Build a systematic sim-to-real transfer pipeline, connecting existing simulation infrastructure to training.
• Deploy and iterate learned policies on physical robot hardware.
• Mentor junior researchers and engineers, and publish at top-tier venues.

Skills and requirements

• PhD/MSc in ML, Robotics, CS, or related field with 4+ years of equivalent industry research experience.
• Demonstrated expertise training and deploying learned manipulation policies on real robots.
• Strong background in at least two of: behaviour cloning, diffusion policies, VLA/VLM architectures, RL for manipulation.
• Track record of publications at top-tier venues (CoRL, RSS, ICRA, NeurIPS, ICML, ICLR), or equivalent demonstrated research impact through deployed systems, patents, or significant.

Confirmed role details

• Develop policies that generalise across tasks, object categories, and environments.
• Design hierarchical behaviour systems for long-horizon manipulation.
• Drive systematic ablations across architectures.
• Build the sim-to-real transfer pipeline: domain randomisation, rendering augmentation, sim-to-real benchmarking.

Candidate fit

• technical judgement, safe working habits, careful diagnostics, and practical problem-solving