Reinforcement Learning Engineer - Manipulation
Humanoid London
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.