Applied Scientist II, Reinforcement Learning

What you’d do

Design and implement whole-body control methods for balance, locomotion, and dexterous manipulation, using learned and model-based control. Build robust real-time controllers with stability guarantees and collaborate with multi-disciplinary teams on hardware and algorithm co-design. Full-time. Found on the employer's careers page on Oct 6, 2026. Apply through the link.

You’ll need

• PhD, or Master's degree and 2+ years of CS, CE, ML or related experience
• Experience with imitation and reinforcement learning for whole-body control
• Experience with hierarchical quadratic programming and model-predictive control
• Experience with simulation environments such as IsaacLab, Mujoco, Drake