humanoid - Reinforcement Learning Engineer - Manipulation
Requirements
• 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it. • Hands‑on with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference. • Experience solving real problems using reinforcement learning with deep neural networks in any domain. • Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. • You are self-driven, pro-active, communicate efficiently, document experiments clearly and communicate trade‑offs crisply. • Experience with simulators for robotics (Isaac Sim, MuJoCo etc.) • Experience building infrastructure for large-scale RL (e.g. using ray). • Publications at ICLR/ICML/NeurIPS or equivalent open‑source contributions. • Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks.
Responsibilities
• Train language-vision conditioned manipulation policies via reinforcement learning (RL) in simulation and in the real world. • Construct challenging and diverse suites of manipulation tasks in simulation. • Partner with teleoperations to collect trajectories in simulation for behavior cloning. • Partner with testing and operations to establish real-world RL training pipelines. • Experiment with various ways of bringing policies trained in simulation to the real world.
Benefits
• Competitive equity: stock options with meaningful upside as we scale. • 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). • Private healthcare, including virtual and in-person care. • Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. • Free daily breakfast, catered lunch, and snacks in-office. • Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. • Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.
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