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, evaluation infrastructure, and research tools.
- Build and lead the research team. Recruit and develop exceptional researchers and engineers, partner with leading labs, and publish consequential research.
What We're Looking For
- Deep Physical AI expertise. Significant experience in robotics, embodied AI, robot learning, autonomous systems, or related fields.
- Strong learning and agentic systems intuition. Deep understanding of modern robot learning, multimodal models, imitation learning, reinforcement learning, world models, planning, and control.
- Physical systems intuition. Strong understanding of sensing, calibration, control, contact, actuation, latency, uncertainty, and hardware constraints.
- Exceptional research taste. You identify problems that can meaningfully expand what AI systems can do in the physical world.
- Experimental rigor. You turn open questions into strong hypotheses, controlled experiments, meaningful baselines, and evidence-backed conclusions.
- Strong evaluation judgment. You understand generalization, distribution shift, benchmark design, hardware-specific effects, and the failure modes of physical AI evaluations.
- Systems thinking. You reason across models, agents, data, hardware, simulation, tools, and evaluation as parts of a single system.
- Technical range. You are comfortable moving between model training, agent design, simulation, evaluation infrastructure, and physical experimentation.
- Research leadership. You have experience setting direction, mentoring exceptional technical talent, and leading ambitious research programs under uncertainty.
Preferred Qualifications
- Master's or PhD in Robotics, Computer Science, AI, Machine Learning, Engineering, or a related field.
- Research experience at a leading AI, robotics, or embodied intelligence organization.
- Strong publication record at venues such as CoRL, RSS, ICRA, IROS, NeurIPS, ICML, or CVPR, or equivalent high-impact technical work.
- Experience with generalist robot policies, cross-embodiment learning, robot foundation models, or large-scale imitation and reinforcement learning.
- Hands-on experience with robotic platforms and frameworks such as ROS/ROS2, Isaac Lab, MuJoCo, ManiSkill, or equivalent systems.
- Experience building robotics benchmarks, simulation environments, teleoperation systems, safety evaluations, or physical-world data engines.
- Experience building agents for engineering, scientific, manufacturing, or laboratory workflows.
Compensation & Benefits Notice
The national pay range for this full-time position is base salary of $250,000 $350,000. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce.
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