Machine Learning & Robotics Scientist

Why are We Hiring for this Role:

• Design, develop, and optimize reinforcement learning algorithms with world models 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.
• Analyze and optimize control performance with a focus on robustness, energy efficiency, and adaptability.
• Contribute to the continuous development of our in-house training pipelines and tooling.

What Kind of Person We Are Looking For:

• Proficiency in Python and C++ for algorithm development and deployment.
• 2+ years of experience in machine learning (NNs, LVMs, VLAs) and reinforcement learning applied to robotics or similar real-time environments.
• Hands-on experience with physics simulation environments (e.g., MuJoCo, Isaac Lab).
• Experience with deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).
• Strong understanding of classical and modern control theory, locomotion dynamics, etc.
• Experience working with physical robots.
• Contributions to open-source ML or robotics projects.
• M.Sc. or Ph.D. in Robotics, Computer Science, Mechanical Engineering, or a related field.
• Publication record in the field.