Job Description
Responsibilities
- Develop and deploy manipulation policies for dexterous task execution on physical robots
- Build grasp planning and contact-rich control pipelines that generalize across varied objects and environments
- Design and run data collection and teleoperation infrastructure to feed policy training at scale
- Train manipulation policies using imitation learning, reinforcement learning, or hybrid approaches
- Integrate manipulation with the perception stack and broader autonomy pipeline
- Diagnose failure modes on hardware systematically and drive improvements
Requirements
- Strong foundations in robotics, control theory, and motion planning
- Hands-on experience with manipulation systems on real robotic platforms, gained through industry or research work
- Proficient in Python and C++, with PyTorch or JAX experience
- Experience taking manipulation...