Machine Learning: Whole-Body Control

The role

You will train low-level control policies in simulation. You will 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.

Required qualifications

• Very strong coding skills in Python, C++, or Rust.
• Strong foundations in modern reinforcement learning.
• Experience training embodied control policies.
• Hands-on robotics simulation experience.
• Solid intuition for dynamics, contact, and actuation.
• Comfortable running large-scale GPU experiments.

Nice to have

• CUDA is a plus

About the company

The Bot Company is a small team of engineers, designers, and operators based in San Francisco building a helpful robot for every home.