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Job description
Vice President, Robot Learning
Confidential | Early-Stage Robotics Startup | San Francisco Bay Area, CA
About the Opportunity
We're partnering with an ambitious early-stage robotics company building the next generation of humanoid telepresence systems for industrial work.
The company's mission is to make dangerous, highly skilled physical work safer and more accessible by enabling expert operators to remotely control humanoid robots with real-time visual, auditory, and haptic feedback. These systems are deployed in complex environments including energy infrastructure, industrial facilities, manufacturing, and other hazardous settings.
A core part of the long-term vision is transforming teleoperation data into increasingly autonomous robotic capabilities. Rather than treating teleoperation as a temporary solution, the company views it as the foundation for building high-quality robot learning systems based on real-world interaction, force feedback, and task execution.
This is an opportunity to define the robot learning strategy at a company where machine learning is central to the product roadmap.
The Role
We're seeking a Vice President of Robot Learning to lead the company's robot learning organization and own the roadmap from teleoperation data collection through to learned policies and increasing levels of autonomy.
This is a highly technical leadership role for someone who enjoys building from first principles, working closely with hardware and software teams, and translating cutting‑edge robotics research into production systems.
You'll have the opportunity to shape both the technical direction and the team as the company scales.
What You'll Do
Own the robot learning strategy and technical roadmap.
Build the data pipeline that transforms teleoperation sessions into high-quality training data.
Develop learning systems for contact‑rich robotic manipulation using real-world demonstrations.
Design and deploy imitation learning, reinforcement learning, and policy optimization approaches for physical robots.
Work closely with robotics, controls, perception, and hardware engineers to build an integrated robotic system.
Lead the evolution from teleoperated workflows toward 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 operational data.
What We're Looking For
Required
PhD or equivalent expertise in Robotics, Machine Learning, Computer Science, or a 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.
Experience working with physical robots rather than purely simulated environments.
Strong understanding of contact-rich manipulation, force feedback, and real-world robotic control.
Track record of shipping robotics systems from research into production.
Experience leading highly technical teams or serving as the technical leader for a major robotics initiative.
Preferred
Experience from leading robotics organizations or research groups such as:
OpenAI Robotics
Google DeepMind Robotics
Physical Intelligence
Toyota Research Institute
Figure AI
Agility Robotics
Covariant
Skild AI
Sanctuary AI
Dexterity
Intrinsic
Boston Dynamics
Other leading manipulation or humanoid robotics companies
Particularly valuable experience includes:
Learning from teleoperation or human demonstrations
Building commercial robot learning data pipelines
Manipulation in contact-rich environments
Haptic interfaces or force-controlled robotics
Multi-modal learning using vision, force, and proprioception
Scaling robot learning infrastructure across fleets
Who You Are
Builder-first with a passion for deploying robotics in the real world.
Comfortable operating in an early-stage, fast-moving environment.
Excited by ambiguous technical problems with significant ownership.
Able to balance long-term research vision with near-term product execution.
Motivated by building a team, not just contributing individually.
Collaborative, hands‑on, and deeply technical.
Why Join
Define the robot learning strategy from an early stage.
Build systems that operate in challenging, real-world industrial environments.
Work across hardware, controls, perception, and AI to solve end-to-end robotics problems.
Help shape the future of intelligent humanoid robotics.
Significant technical ownership with the opportunity to build and lead a high-impact organization.
Location: San Francisco Bay Area, California (onsite)
Employment Type: Full-time
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Worksite address
palo alto, CA, 94306, US
Who can apply
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