Robot learning engineer
Core
Design and implement state-of-the-art learning algorithms for robot manipulation, navigation, and control, scaling ML systems for large-scale model training and fine-tuning to enhance robot dexterity and mobility.
Role type
Senior IC robot learning engineer (physical AI)
Builds
Robotic manipulation and navigation systems for physical hardware
Domain
Robotics + Machine Learning
Deliverable
production ML models
Required skills
Reinforcement learning, imitation learning, behavior cloning, Python, PyTorch, TensorFlow, JAX, robot simulators (Isaac Gym, Isaac Sim, MuJoCo, SAPIEN, Drake), real robot experimentation, debugging complex robotic systems
Preferred skills
Vision-language models, foundation models for robotics, sim-to-real transfer, domain randomization, distributed training, MLOps infrastructure, manipulation/grasping expertise, prototype-to-production track record
Technologies
Isaac Gym, Isaac Sim, MuJoCo, SAPIEN, Drake, PyTorch, TensorFlow, JAX
Responsibilities
Design and implement learning algorithms for robot manipulation, navigation, and control; Develop novel approaches using reinforcement learning, imitation learning, and foundation models; Scale ML systems for large-scale model training and fine-tuning; Build diverse, robust manipulation skills; Collaborate with hardware, controls, and systems engineers
Seniority
Senior, hands-on IC
