Machine Learning: Whole-Body Control

Pantera Capital; San Francisco (CA); On-site; USD 200,000 - 350,000; Full time

Benefits offered by this job

Comprehensive benefits package including medical, dental, and vision coverage

Access to a 401(k) plan

Equity through the company's discretionary equity program

Job summary

A technology-focused company in San Francisco seeks candidates for a role specializing in robotic control systems. You will train whole-body policies, build simulation environments, and run GPU training experiments. Ideal candidates should have strong coding skills in Python, C++, or Rust, and a solid understanding of reinforcement learning principles. The position offers a competitive compensation range of $200K to $350K, and you’ll work with a small, elite team in a dynamic, high-performance environment.

Qualifications

• 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.
• Design rewards and curricula for stable long-horizon learning.
• Own sim-to-real transfer using domain randomization.
• Run and debug large-scale GPU training experiments.

Skills

Strong coding skills in Python

Strong coding skills in C++

Strong coding skills in Rust

Experience in CUDA

Foundations in modern reinforcement learning

Robotics simulation experience

Intuition for dynamics, contact, and actuation

Experience with large-scale GPU experiments

Job description

Location

San Francisco

Employment Type

Full time

Department

Engineering Software

Compensation

• $200K – $350K

Actual compensation will depend on skills, experience, and qualifications.

Base salary is one part of the total compensation package. The role is also eligible for equity through the company’s discretionary equity program, along with a comprehensive benefits package that includes medical, dental, and vision coverage, and access to a 401(k) plan.

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.

Machine Learning: Whole-Body Control

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.

Why Join

You'll work with a small, elite team on challenges that require speed, intelligence, and deep engineering instinct. If you enjoy understanding systems at all levels, move fast, and think even faster, you'll thrive here.

Compensation Range: $200K - $350K