Staff Research Engineer, Robot Learning Systems

Required

• Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or related field with significant relevant experience, or a PhD degree.
• Track record of leading complex robotic or embodied systems end-to-end and setting technical direction for other engineers.
• Strong proficiency in both C++ and Python, with solid systems programming and real-time / performance-critical engineering skills.
• Hands-on experience with ROS/ROS2 and robot middleware, including real-time integration of sensing, control, and compute.
• Experience integrating and deploying ML models/policies into real-time robotic or autonomous systems — system ownership and building, rather than model training or research.
• Requires 5 days/week in-office collaboration with the teams.
• Bonus Qualifications
• Experience with teleoperation and data-collection systems (e.g., VR, UR, GELLO, UMI) and the challenges of collecting high-quality robot data at scale.
• Experience with on-robot reinforcement learning or closed-loop policy-improvement systems.
• Familiarity with robot learning policies (VLA, imitation learning, behavior cloning) and their real-time inference and control-integration characteristics.
• Familiarity with manipulation stacks, whole-body control interfaces, or real-time middleware tuning.