Research Fellow (Robot Learning & Manipulation)
Core
Lead research and development of learning-based visuomotor policies for humanoid robot manipulation, focusing on real-robot deployment and novel contributions.
Role type
Senior IC research fellow (robot learning & manipulation)
Builds
Visuomotor manipulation policies for humanoid robots (grasping, bimanual manipulation, assembly)
Domain
Robotics, Artificial Intelligence, Humanoid Robotics
Deliverable
production ML models
Required skills
robot learning, visuomotor control, behavior cloning, reinforcement learning, deep learning frameworks, Python, real-robot deployment, research problem definition, project management
Preferred skills
humanoid robotics, dexterous platforms, industry collaboration, commercialization
Technologies
PyTorch, deep learning frameworks
Responsibilities
Define research directions and technical roadmaps for manipulation capabilities; advance techniques including behavior cloning, reinforcement learning, and VLA-based reasoning; develop approaches to robustness challenges; oversee the research pipeline from data collection to deployment; supervise and mentor research associates, engineers, and PhD students; collaborate with perception, controls, systems, and hardware teams; evaluate tradeoffs between learning-based and classical approaches; lead preparation of publications and technical reports.
