ML, Reinforcement Learning

From the original posting

Redwood City ABOUT THE ROLE You will own reinforcement learning across our stack, from locomotion policies to RL applied on top of learned behaviors. The research problems here are open ones: whole-body control under contact, sim-to-real transfer that holds up in environments we have never seen, and learning from a growing body of real-world robot experience. This is a role for someone who wants their research to run on hardware in the field rather than on a benchmark, and who is early enough in a team's life to set its technical direction. WHAT YOU'LL DO - Own RL across our stack, from…