VP of Robotics Research

Job Title: VP of Robotics Research Job Type: Full-time Location : Remote The Role As VP of Robotics Research at micro1, you will define and lead our research agenda for Physical AI — intelligent systems that can understand, reason about, and act in the physical world. Our research focuses on four connected areas: Physical Agents & Robotics — building agents that perceive, reason, plan, and act through robots, machines, instruments, and other physical systems. Learning & Data — studying how demonstrations, trajectories, sensor data, simulation, feedback, and autonomous experience improve physical-world intelligence. Evaluation & Generalization — developing rigorous methods to measure physical reasoning, manipulation, planning, robustness, safety, and transfer across tasks and environments. Physical-World R&D Automation — exploring how agents can accelerate scientific and engineering workflows through simulation, experimentation, design, fabrication, and real-world tools. You will set research direction across these areas, stay close to models and physical systems, build a world-class research team, and partner with leading AI and robotics labs on their hardest Physical AI problems. What You’ll Do Set the Physical AI research agenda. Identify the highest-leverage problems across robotics, embodied agents, learning, data, evaluation, and physical-world automation. Build agents that act in the physical world. Develop systems that connect foundation models and agents to robots, machines, instruments, and other physical interfaces. Advance general-purpose robot learning. Lead research across vision-language-action models, imitation learning, reinforcement learning, world models, and multimodal policies. Develop a science of physical-world data. Study which demonstrations, trajectories, sensor streams, environments, and supervision signals best improve learning and generalization. Build scalable data-generation systems. Develop methods for generating high-quality interaction data through human demonstration, teleoperation, autonomous rollout, simulation, and hybrid human–agent workflows. Advance evaluation and generalization. Build rigorous benchmarks for manipulation, spatial reasoning, planning, tool use, robustness, safety, and transfer across tasks and embodiments. Bridge simulation and reality. Study how simulated and real-world experience should be combined and where sim-to-real transfer breaks down. Advance physical-world R&D automation. Build agents that operate across scientific and engineering workflows, including simulation, experimentation, design, fabrication, and laboratory systems. Build research that compounds. Create reusable datasets, environments, simulators, hardware testbeds, evaluati