Senior Reinforcement Learning Engineer

Highlights

• Drive world-class locomotion and manipulation on humanoid robot Apollo.
• Take RL policies from simulation to robust deployment on physical hardware.
• Translate human mocap and teleoperation into reference trajectories for RL.

Ideal candidate

Hands-on roboticist with deep RL expertise who thrives taking learning from sim to real humanoids and mentoring others to push world-class performance.

Requirements

• 5+ years hands-on expertise with RL frameworks and physics simulators
• Mastery of Python for prototyping and proficiency in C++ for deployment
• Experience building or utilizing large-scale distributed training pipelines
• Strong understanding of modern RL including imitation, model-based and sim-to-real
• Intuition for robot dynamics and controls theory
• PhD or MS in Computer Science, Robotics or related field with 2+ years industry experience preferred
• Proven track record deploying learning-based policies on physical robots
• Experience mentoring engineers