Research

VP of Robotics Research

Status: Open

Micro1

Pay
$100–$120/hr
Location
Remote
Employment type
Full-time
Openings
1
Start
less-than-7-days
Posted
2026-09-17

About this opportunity

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. micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to support@micro1.ai. Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.

Required skills

  • Robotics Software
  • Robotics Data
  • Robotics Research

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.

Requirements

  • 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

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.
AI TrainingMicro1

Senior AI Trainer

Evaluate AI chat and search tools, grade model responses, write and refine prompts, and provide structured feedback for AI training.

Contractor· Remote — Northern America and Europe

Status: Open

$14–$36/hr

Verified Oct 3, 2026

Apply → (opens in a new tab)
AI TrainingMicro1

Software Engineer

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Contractor· Remote

Status: Open

$30–$100/hr

Verified Oct 3, 2026

Apply → (opens in a new tab)
CodingMicro1

TypeScript + Rust Developer

Job Title: TypeScript + Rust Developer Job Type: Contractor Location: Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Key Responsibilities: - Collaborate with cross-functional teams to deliver robust solutions in TypeScript and Rust. - Design, implement, and refactor complex systems, with a focus on codebase migrations or rewrites between language ecosystems. - Create and curate high-quality human data for AI training and evaluation tasks. - Follow best practices for software engineering, including code reviews, testing, and documentation. - Communicate technical concepts clearly via written and verbal communication to both technical and non-technical stakeholders. - Troubleshoot, debug, and optimize codebases in both TypeScript and Rust environments. - Maintain 6+ hours of daily work overlap with the Eastern Time zone to ensure effective collaboration. Required Skills and Qualifications: - 5+ years of professional software development experience, with a proven track record of production-level work. - Idiomatic fluency in TypeScript and Rust, demonstrated through hands-on experience. - Strong background in codebase migrations, rewrites, or working within multiple language environments. - Excellent written and verbal communication skills, with the ability to explain complex technical issues clearly. - Experience producing or working with human-labeled data, ideally for AI or ML applications. - Ability to work independently and as part of a remote, global team. - Fluent English proficiency. Preferred Qualifications: - Previous experience on AI/ML data engineering or data labeling teams. - Contributions to open-source TypeScript or Rust projects. - Background in developing scalable cloud-native applications.

Contractor· Remote

Status: Open

$30–$100/hr

Verified Oct 3, 2026

Apply → (opens in a new tab)