2 months ago
London, United KingdomMid Level
Responsibilities
- Train language-vision-conditioned manipulation policies with reinforcement learning in simulation and the real world.
- Construct challenging and diverse manipulation-task suites in simulation.
- Partner with teleoperations to collect simulation trajectories for behavior cloning.
- Work with testing and operations to establish real-world reinforcement-learning training pipelines.
- Experiment with methods for transferring policies from simulation to the real world.
Requirements
- 3+ years of experience building deep-learning systems in industry or research, with shipped models or published artifacts.
- Hands-on experience with at least one of LLMs, VLMs, or image/video generative models, including architecture, training, and inference.
- Experience solving real problems with reinforcement learning and deep neural networks.
- Strong Python and PyTorch or JAX skills, including profiling, numerical debugging, and maintainable research-code development.
- Experience with robotics simulators such as Isaac Sim or MuJoCo is preferred.
- Experience with reinforcement learning for robotics is preferred.
- Experience building infrastructure for large-scale reinforcement learning, such as using Ray, is preferred.
- Publications at ICLR, ICML, NeurIPS, or equivalent open-source contributions are preferred.
- Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks is preferred.
Benefits
- Competitive equity through stock options with meaningful upside.
- 30+ paid days off, including 23 days of annual leave, UK bank holidays, and additional company closure days.
- Private healthcare with virtual and in-person care.
- Pension scheme with an 8% total contribution, comprising 5% employee and 3% employer contributions, on full earnings.
- Free daily breakfast, catered lunch, and snacks in the office.
- London-based role with in-office collaboration.
- Opportunity to work with engineers, researchers, and product experts on humanoid robotics and AI.
- Direct access to founding leadership and meaningful input into product direction.
Categories
ML EngineeringRobotics
