Machine Learning: Whole-Body Control
The Bot Company, San Francisco
The role
We are building high-performance whole-body controllers that produce robust, agile motion and manipulation in the real world.
You will train low-level control policies in simulation and own the stack from environment design to large-scale training and sim-to-real deployment.
What you will do
- Train whole-body policies for locomotion, manipulation, and coordinated motion.
- Build scalable simulation environments in IsaacLab, MuJoCo, or similar with parallel rollouts.
- Design rewards and curricula that enable stable long-horizon learning.
- Own sim-to-real transfer using domain randomization and structured evaluation.
- Run and debug large-scale GPU training experiments.
