AI Engineer (RL & WBC)

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 software development experience, including CI/CD, unit testing, etc.
• 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.

Benefits

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