Machine Learning: Whole-Body Control

The Bot Company

We're building a helpful robot for every home.

We're a small team of engineers, designers, and operators based in San Francisco. Our team comes from Tesla, Cruise, OpenAI, Google, Pixar, and many other great companies. In the past we've shipped to hundreds of millions of users and know what it takes to build amazing products and experiences.

Our team is deliberately lean to promote rapid decision making and do away with bureaucracy and hierarchy. Everyone is an IC and is empowered with massive scope, radical ownership, and direct responsibility. We work across the stack with a culture built for rapid iteration and fast execution.

What We Look for in All Candidates

All roles at The Bot Company demand extreme sharpness and the ability to move fast in high-intensity environments. Throughout the process, we expect candidates to demonstrate:

• Exceptional mental acuity: you think quickly, learn instantly, and reason across unfamiliar domains.
• Engineering curiosity: you naturally dig into how systems work, even outside your specialty.
• High performance mindset: you move fast, handle ambiguity, and excel when the environment is demanding.

About 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'll 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.

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.