VP of Robotics Research

Lead the research agenda for Physical AI, creating intelligent systems that can perceive, reason about, and act in the physical world. This role shapes ambitious work at the intersection of robotics, embodied agents, learning, data, evaluation, and physical-world research and development automation.

You will set research direction across Physical AI, remain closely involved with models and physical systems, build a high-caliber research team, and collaborate with leading AI and robotics labs on complex Physical AI challenges.

• Define the Physical AI research agenda and identify high-leverage opportunities across robotics, embodied agents, learning, data, evaluation, and physical-world automation.
• Develop agents that connect foundation models to robots, machines, instruments, and other physical interfaces.
• Lead work on general-purpose robot learning, including vision-language-action models, imitation learning, reinforcement learning, world models, and multimodal policies.
• Research how demonstrations, trajectories, sensor streams, environments, and supervision signals improve learning and generalization.
• Build scalable interaction-data generation methods using human demonstration, teleoperation, autonomous rollouts, simulation, and hybrid human-agent workflows.
• Create rigorous benchmarks for manipulation, spatial reasoning, planning, tool use, robustness, safety, and transfer across tasks and embodiments.
• Study how simulated and real-world experience can be combined, including limitations in simulation-to-reality transfer.
• Develop agents that support scientific and engineering workflows such as simulation, experimentation, design, fabrication, and laboratory systems.
• Create reusable datasets, environments, simulators, hardware testbeds, evaluation infrastructure, and research tools.
• Recruit, develop, and lead researchers and engineers; collaborate with leading labs; and publish consequential research.

• Significant experience in robotics, embodied AI, robot learning, autonomous systems, or a related field.
• Deep expertise in Physical AI.
• Strong intuition for learning systems and agentic systems.
• Skills in robotics software, robotics data, and robotics research.

Full-time, remote role.

Annual compensation of $1, 200, 000 to $6, 000, 000.