VP, Robot Learning & Autonomy for Industrial Humanoids

HIKINEX; Palo Alto (CA); On-site; USD 220,000 - 420,000; Full time

Job summary

Confidential in the San Francisco Bay Area, CA is seeking a Vice President of Robot Learning to lead the robot learning organization and own the roadmap from teleoperation data collection through learned policies and higher levels of autonomy.

This highly technical leadership role requires building from first principles, collaborating with hardware and software teams, and translating cutting-edge robotics research into production systems.

Qualifications

• PhD or equivalent in Robotics, ML, CS, or related field.
• Significant experience building robot learning systems for real-world robotic manipulation.
• Deep expertise in imitation learning, reinforcement learning, policy learning, or related techniques.

Responsibilities

• Own the robot learning strategy and technical roadmap.
• Build data pipeline transforming teleoperation sessions into high-quality training data.
• Develop learning systems for contact-rich manipulation from real-world demonstrations.
• Design and deploy imitation learning, reinforcement learning, and policy optimization approaches for physical robots.
• Collaborate with robotics, controls, perception, and hardware engineers to build an integrated system.
• Lead evolution from teleoperation to progressively autonomous capabilities.
• Build, mentor, and grow a world-class robot learning organization.
• Establish technical direction, research priorities, and engineering best practices.
• Drive experimentation, deployment, and continuous improvement using real-world data.

Skills

PhD/related field

Robot learning systems

Imitation learning

Reinforcement learning

Real-world robotics

Production deployment

Technical leadership

Education

PhD in Robotics/CS/ML

Job description

Confidential in the San Francisco Bay Area, CA is seeking a Vice President of Robot Learning to lead the robot learning organization and own the roadmap from teleoperation data collection through learned policies and higher levels of autonomy.

This highly technical leadership role requires building from first principles, collaborating with hardware and software teams, and translating cutting-edge robotics research into production systems.