Machine Learning Engineer - Humanoid Robotics
Core
Developing foundation models and algorithms for humanoid robot locomotion and manipulation, transferring research to production systems.
Role type
Senior IC machine learning engineer (humanoid robotics)
Builds
Isaac Loco-Manipulation team products, including GR00T and Cosmos foundation models
Domain
Robotics, specifically humanoid loco-manipulation and mobile manipulation
Deliverable
production ML models
Required skills
deep learning frameworks (PyTorch, JAX, TensorFlow), physics simulation tools (Isaac Sim/Lab, MuJoCo), foundation models for robotics, 3D perception, sim-to-real transfer, robot learning (imitation, reinforcement learning), C++, Python
Preferred skills
human video learning, human-object reconstruction, dexterous bimanual manipulation, whole-body control, robotics research publications
Technologies
Isaac Lab, Newton, Isaac Sim, MuJoCo
Responsibilities
Define and execute projects in humanoid robotics loco-manipulation, develop reference workflows for dexterous tasks, advance technologies for robot learning and synthetic data generation, design and deploy algorithms for robot locomotion and manipulation, transfer innovations into products including prototypes and open source software, drive full development lifecycle from design to on-robot validation
Seniority
Senior, hands-on IC
