Robotics AI Engineer

Highlights

• Train policies that run on Asimov humanoid in the real world.
• Ship to real robots and open-source everything you can.
• See your work move physical hardware within days, not quarters.

Ideal candidate

Empirical roboticist who loves getting policies working on real hardware. You thrive on fast iteration, debugging failures, and collaborating across hardware and software to make humanoids useful.

Requirements

• Strong foundations in reinforcement learning or imitation learning, with hands-on experience training policies that run on real systems
• Comfort working directly with robots, not just simulators
• Proficiency in Python and familiarity with standard RL/ML frameworks (JAX, PyTorch, IsaacGym/IsaacLab, MuJoCo, or similar)
• An empirical, debugging-first mindset, you care about what actually works on hardware
• Ability to move fast and context-switch between research problems and engineering tasks