Humanoid · 11–50 people · Series A
Reinforcement Learning Engineer - Manipulation
- London
- On-site
- Mid-level
- Permanent
Train language-vision conditioned manipulation policies using reinforcement learning in both simulation and the real world, building task suites and real-world RL pipelines. Work closely with teleoperations and testing teams to collect trajectories and transfer policies from simulation to physical robots. Requires deep-learning experience with Python and PyTorch/JAX, plus hands-on work with LLMs, VLMs or generative models.
Isaac Sim · MuJoCo · Ray +2