AI Engineer (RL & WBC)

Foundation Robotics Lab; San Francisco (CA); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Health insurance

Vision insurance

Dental insurance

401k

Job summary

An innovative robotics company in San Francisco is seeking engineers to design and develop advanced reinforcement learning algorithms for humanoid robots. Ideal candidates should have experience in machine learning applied to robotics, proficiency in Python and C++, and familiarity with physical simulation environments. This role offers a chance to contribute to groundbreaking technology while joining a mission-driven team dedicated to reducing human risk and increasing efficiency in various industries.

Qualifications

• 2+ years of experience in reinforcement learning applied to robotics or similar environments.
• Experience deploying RL algorithms on physical robots.
• Contributions to open-source RL, ML or robotics projects.

Responsibilities

• Design, develop, and optimize reinforcement learning algorithms.
• Integrate learned policies into real-world robot platforms.
• Collaborate with teams to ensure integration between hardware and software.

Skills

Machine learning (NNs, LVMs)

Hands-on experience with physics simulation environments

Proficiency in Python

Proficiency in C++

Experience with deep learning frameworks

Familiarity with ROS/ROS2

Strong understanding of control theory

Education

M.Sc. or Ph.D. in Robotics, Computer Science, Mechanical Engineering

Tools

MuJoCo

Isaac Lab

PyTorch

JAX

TensorFlow

Job description

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 on the lookout 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 expect that many of our team members will bring diverse perspectives from various industries and fields. We are looking for individuals with a proven record of exceptional ability and a history of creating things that work.

Our Culture

We like to be frank and honest about who we are, so that people can decide for themselves if this is a culture they resonate with. Please read more about our culture here https://foundation.bot/culture.

Who should join:

• 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 - regardless of the role you are in. We are building 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.

Why are We Hiring for this Role:

• 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.

What Kind of Person We Are Looking For:

• 2+ years of experience in machine learning (NNs, LVMs) and reinforcement learning applied to robotics or similar realtime environments.
• Hands-on experience with physics simulation environments (e.g., MuJoCo, Isaac Lab).
• Proficiency in Python and C++ for algorithm development and deployment.
• Experience with deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).
• Familiarity with ROS/ROS2 and real-time robotic systems.
• Strong understanding of classical and modern control theory, locomotion dynamics, etc.
• Experience deploying RL algorithms on physical robots.
• Experience with high-performance computing for distributed training.
• Contributions to open-source RL, ML 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, 401k, etc.). Join us for the culture and the mission, not for the benefits.