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Pioneering Embodied AI: Why Elite Robotics Researchers Are Joining micro1 as a Member of Technical Staff ($500K–$1.5M/yr Total Comp)

Company: micro1 · Pay: $200000–$320000/year · Location: Remote — Worldwide · Type: full time · Posted: 2026-09-16

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The next great frontier in artificial intelligence extends far beyond digital text generation and chat interfaces into the physical world. Embodied AI, world models, and advanced robotics are reshaping automation, manufacturing, and spatial intelligence. However, the primary bottleneck holding back modern robotics is not hardware engineering—it is data quality, dataset architecture, and scalable simulation pipelines.

micro1—the premier AI data lab powering frontier model training and agent evaluations—is scaling its core research division through a high-impact full-time opening: the Member of Technical Staff, Robotics Research role. Offering an elite compensation package ranging from $200,000 to $320,000 base salary plus substantial equity participation (pushing total compensation potential between $500K and $1.5M/year), this remote-first position places top-tier robotics scientists at the helm of physical AI data innovation.

Whether you are a machine learning researcher specializing in multimodal perception, a robotics engineer looking to lead data strategy at scale, or an industry expert eager to work with leading AI and robotics labs, this guide provides an in-depth breakdown of the role responsibilities, required qualifications, compensation structure, and how to complete your application.

Member of Technical Staff, Robotics Research

$500K - $1.5M / yr
Base Salary Range $200,000 - $320,000 USD
Total Compensation $500K - $1.5M/yr (incl. Equity)
Work Format Remote-First / Core Team
Core Focus Robotics Data & Embodied AI

Role Overview: Research and design the datasets, collection methods, and evaluation frameworks that power next-generation robot learning, spatial reasoning, and perception systems for physical AI.

Required Skills & Competencies:
Robotics Data Robot Perception Schema Design Robotics R&D Multimodal Learning Dataset Architecture Spatial Reasoning Technical Communication

The Core Mission: Solving the Data Bottleneck in Physical AI

While large language models benefit from massive text corpuses scraped from the internet, robotic systems require rich, multi-modal, physics-grounded data streams. From egocentric video feeds and teleoperation trajectories to sensor integration and simulation environments, training a robot to navigate, manipulate objects, and reason spatially demands rigorous dataset curation.

As a Member of Technical Staff in Robotics Research at micro1, you will sit at the exact intersection of robotics, embodied AI, and scalable data systems. Your work will directly define how frontier AI labs train robotic agents to interact safely and effectively with the physical world.

What You Will Do:

  • Data Needs Research: Investigate and map out the data requirements of frontier robotics, world models, and physical AI systems.
  • Dataset Architecture: Design innovative datasets and collection methodologies spanning egocentric video, teleoperation, Universal Manipulation Interface (UMI), robot trajectories, diverse sensor arrays, and simulation environments.
  • Schema & Evaluation Design: Define data schemas, fine-grained annotations, ground truth metrics, and rigorous evaluation frameworks for manipulation, navigation, spatial reasoning, and physical understanding.
  • Experimental Iteration: Execute empirical experiments to determine precisely which dataset structures and formats yield the highest performance improvements in model training.
  • Ecosystem Collaboration: Partner directly with leading AI and robotics labs, translating complex research challenges into scalable data pipelines and production-ready pipelines.
  • Strategic Foresight: Stay ahead of cutting-edge academic and industrial research, translating insights into micro1’s overarching robotics data strategy.

💡 Maximizing Professional Impact: To thrive in this core team role, candidates should excel at translating abstract research problems into concrete datasets, experiments, and engineering specifications. Networking with top-tier robotics professionals and encouraging peers in your network to explore micro1's ecosystem helps build the human intelligence layer for next-generation AI.

Required Qualifications and Technical Background

Because this is an elite core research position, micro1 maintains rigorous evaluation standards to identify top-tier talent in the robotics and machine learning communities:

  • Professional Experience: 2 to 5+ years of hands-on experience in robotics, computer vision, multimodal learning, embodied AI, or applied machine learning research.
  • Domain Mastery: A deep, intuitive understanding of physical AI, robotic kinematics, perception pipelines, and multimodal data structures.
  • Translational Acumen: Proven ability to convert high-level research objectives into structured datasets, repeatable experiments, and precise technical specs.
  • Communication Skills: Exceptional technical communication and cross-functional collaboration abilities.
  • Educational Background: A degree in Robotics, Computer Science, Electrical Engineering, Machine Learning, or a related technical field (or equivalent professional experience).

Bonus Qualifications (What Sets Top Candidates Apart):

  • Prior tenure at a leading robotics research lab, autonomous vehicle company, or frontier AI enterprise.
  • Practical experience with embodied AI datasets, imitation learning, teleoperation frameworks, or robot learning pipelines.
  • Familiarity with designing multimodal robotics datasets encompassing video, sensor logs, motion trajectories, or synthetic simulation data.
  • Hands-on hardware prototyping experience, including sensor integration and embedded systems.

Unmatched Compensation, Benefits, and Remote-First Culture

micro1’s compensation philosophy reflects the extreme value placed on elite engineering talent. The total rewards package is designed to compete with top-tier Silicon Valley tech labs:

  • Competitive Base Salary: Annual base compensation ranging from $200,000 to $320,000 USD.
  • Significant Equity Participation: All full-time employees are eligible for equity compensation, enabling total annual compensation packages between $500K and $1.5M/year.
  • Comprehensive Health Coverage: Up to 100% reimbursement for health insurance premiums.
  • Robust Benefits: Generous paid time off (PTO), a 401(k) retirement plan with company matching, and comprehensive support for a remote-first work culture.

Step-by-Step Guide to Completing Your Application Successfully

Securing an interview for this core research role requires a meticulous and polished presentation of your academic and engineering credentials. Follow these steps:

  1. Highlight Your Robotics & Dataset Portfolio: Ensure your resume prominently features your work in embodied AI, computer vision, trajectory data collection, or robotic perception systems.
  2. Emphasize Research Impact: Detail specific projects where you bridged theoretical machine learning research with practical data pipeline implementation.
  3. Complete the AI Screening Promptly: micro1 utilizes advanced AI recruitment tools to streamline candidate assessment. Complete all application questions thoroughly and professionally.

Take the next major leap in your engineering career and define the future of physical intelligence.

Responsibilities

  • Data Needs Research: Investigate and map out the data requirements of frontier robotics, world models, and physical AI systems.
  • Dataset Architecture: Design innovative datasets and collection methodologies spanning egocentric video, teleoperation, Universal Manipulation Interface (UMI), robot trajectories, diverse sensor arrays, and simulation environments.
  • Schema & Evaluation Design: Define data schemas, fine-grained annotations, ground truth metrics, and rigorous evaluation frameworks for manipulation, navigation, spatial reasoning, and physical understanding.
  • Experimental Iteration: Execute empirical experiments to determine precisely which dataset structures and formats yield the highest performance improvements in model training.
  • Ecosystem Collaboration: Partner directly with leading AI and robotics labs, translating complex research challenges into scalable data pipelines and production-ready pipelines.
  • Strategic Foresight: Stay ahead of cutting-edge academic and industrial research, translating insights into micro1’s overarching robotics data strategy.

Qualifications

  • Professional Experience: 2 to 5+ years of hands-on experience in robotics, computer vision, multimodal learning, embodied AI, or applied machine learning research.
  • Domain Mastery: A deep, intuitive understanding of physical AI, robotic kinematics, perception pipelines, and multimodal data structures.
  • Translational Acumen: Proven ability to convert high-level research objectives into structured datasets, repeatable experiments, and precise technical specs.
  • Communication Skills: Exceptional technical communication and cross-functional collaboration abilities.
  • Educational Background: A degree in Robotics, Computer Science, Electrical Engineering, Machine Learning, or a related technical field (or equivalent professional experience).

Apply now →