Machine Learning: Whole-Body Control

The Bot Company • San Francisco, CA

6d

About The Position

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.

Requirements

• Very strong coding skills in Python, C++, or Rust. CUDA is a plus.
• 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.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed