We're looking for a Reinforcement Learning (RL) Engineer to develop and deploy learning-based control policies for our robots, including integration with Vision-Language-Action (VLA) stacks. You will own the training loop from simulation and logged data through evaluation on hardware, working closely with simulation, perception, and robotics teams.

This is not a research-only role. You will ship policies that must work under real operational constraints—latency, safety, embodiment differences, and continuous improvement from field data.

• Design, implement, and maintain RL training pipelines for robotic manipulation, navigation, and whole-body control tasks
• Develop and tune policies in simulation and on real hardware, with clear benchmarks for success, robustness, and regression detection
• Integrate RL stacks with VLA and broader autonomy systems: action spaces, planners, low-level controllers, and deployment interfaces <...