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. What you'll do 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 Build reward design, curriculum learning, and domain r...