Key Responsibilities:
- Develop control and learning-based algorithms for humanoid robot locomotion, whole-body control, motion generation, and sim-to-real transfer.
- Contribute to the technical direction of the robotics team by identifying key problems, proposing practical solutions, and helping prioritize engineering efforts.
- Work with simulation, software, hardware, AI, data, and China-based engineering teams to translate robot performance goals into executable plans.
- Mentor other engineers through design reviews, code reviews, experiments, and technical discussions.
Minimum Requirements:
- Master’s or Ph.D. degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
- 5+ years of relevant experience in reinforcement learning, robotics, robot learning, control systems, or related areas.
- Strong background in robot dynamics, control, motion planning, reinforcement learning, imitation learning, or whole-body control.
- Familiarity with modern robot learning methods such as PPO, SAC, behavior cloning, diffusion policies, imitation learning, etc.
- Excellent communication skills, with the ability to work across disciplines, locations, and organizational boundaries.
- Strong ownership mindset and ability to operate effectively in a fast-moving, ambiguous, research-to-product environment.
Preferred Requirements:
- Publications or strong project experience in robotics, reinforcement learning, legged locomotion, humanoid control, or embodied AI are a plus.
- Experience technically leading projects or mentoring other engineers.
- Hands-on experience with legged robot control, testing, or operation.
- A supportive, engaging environment with opportunities to make a significant impact on the future of robotics.
- Opportunities to work on cutting-edge technologies with top talent in the field.
- Competitive compensation, equity, benefits.
- Lunches, snacks, and team activities.