Machine learning & robotics engineer

Machine Learning & Robotics Engineer

Foundation is developing the future of general‑purpose robotics with the goal to address the labor shortage. Our mission is to create advanced robots that can operate in complex environments, reducing human risk in conflict zones and enhancing efficiency in labor‑intensive industries. We are looking for extraordinary engineers and scientists to join our team. Your previous experience in robotics isn't a prerequisite—it's your talent and determination that truly count.

We are a team committed to building technology that matters. We value diverse perspectives from various industries and fields, and we expect our team members to have a proven record of exceptional ability and a history of creating things that work. We are frank and honest about who we are so that people can decide if this culture resonates with them.

Please read more about our culture here (Use the "Apply for this Job" box below)..

• You like working in person with a team in San Francisco.
• You deeply believe that this is the most important mission for humanity and needs to happen yesterday.
• You are highly technical—even if your role is not purely engineering. We build technology; you need to understand technology well.
• You care about aesthetics and design inside out. If it's not the best product ever, it bothers you, and you need to fix it.
• You don't need someone to motivate you; you get things done.

• Design, develop, and optimize reinforcement learning algorithms for real‑time control and locomotion of humanoid robots.
• Integrate learned policies into real‑world robot platforms with hardware‑in‑the‑loop validation.
• Collaborate with mechanical, perception, and embedded systems teams to ensure tight integration between hardware and software.
• Apply advanced techniques such as curriculum learning, domain randomization, and sim2real transfer to improve policy generalization.
• Analyze and optimize control performance with a focus on robustness, energy efficiency, and adaptability.
• Contribute to the continuous development of our in‑house RL training pipelines and tooling.

• 2+ years of experience in reinforcement learning applied to robotics or control systems.
• Strong understanding of classical and modern control theory, locomotion dynamics, and optimization techniques.
• Hands‑on experience with physics simulation environments (e.g., Mu Jo Co , Isaac Gym, PyBullet, Isaac Lab).
• Proficiency in Python and/or C++ for algorithm development and deployment.
• Experience with deep learning frameworks such as PyTorch, Tensor Flow, or JAX.
• Familiarity with ROS/ROS2 and real‑time robotic systems.
• Strong software development experience, including CI/CD, unit testing, etc.
• Experience deploying RL algorithms on physical robots.
• Experience with high‑performance computing for distributed training.
• Contributions to open‑source RL or robotics projects.
• M.Sc. or Ph.D. in Robotics, Computer Science, Mechanical Engineering, or a related field.

We provide market‑standard benefits (health, vision, dental, 401(k), etc.). Join us for the culture and the mission, not for the benefits.

The annual compensation is expected to be between $80,000 and $1,000,000. Exact compensation may vary based on skills, experience, and location.

• Seniority Level: Entry level
• Employment Type:
  
  Full‑time
• Job Function:
  Engineering and Information Technology

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San Francisco, CA