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Robotics Data Generalist - Bay Area

Micro1 Remote Posted 50 days ago

Education

Any

Type

Pay Rate

$17.5/task

Posted

50d ago

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About this Role

Role Overview

We are building real-world datasets used to train robotics systems. This role involves participating in structured data capture sessions designed to generate high-quality training data for embodied AI systems. Participants will follow guided protocols to perform a variety of physical tasks in controlled environments. This is an opportunity to contribute directly to the development of Physical AI.

What You’ll Do

Participate in structured data capture sessions under guided protocols Perform a range of everyday interaction and manipulation tasks Follow detailed instructions to ensure consistency across recordings Help maintain organized data capture workflows Work alongside a small team focused on building high-quality robotics datasets

Who You Are

We are primarily looking for students interested in robotics, AI, and embodied intelligence. Students involved in robotics labs, manipulation research, or control work are especially encouraged to apply. Sessions will take place near the following universities, so anyone able to attend in person nearby is welcome to apply: San Jose State University (SJSU) Santa Clara University (SCU) San Francisco State University (SFSU) University of San Francisco (USF) California State University, East Bay (CSUEB) University of California, San Francisco (UCSF) Golden Gate University

What We’re Looking For

Strong attention to detail Ability to follow structured protocols carefully Reliability and consistency across repeated tasks Interest in robotics and physical AI systems Availability for scheduled data capture sessions Previous robotics experience is helpful but not required. Multi-session availability and eagerness to support longitudinal research projects

Additional Details

Small, selective cohort Multi-session participation preferred Participants will contribute to datasets used to advance robotics research. Data capture sessions will take place in controlled environments near the Bay Area.

Requirements

  • Must be eligible to work in Remote
  • Fluent proficiency in English (Written & Verbal)
  • Reliable high-speed internet connection

Compensation Analysis

Work from anywhere, at any time. This fully remote position ($17.5/hr) breaks down geographic barriers, allowing you to earn US-competitive rates regardless of your local market. It is a perfect stepping stone for building a career in the data labeling and AI training ecosystem.

Skills & Categories

Explore other opportunities in related specializations:

Generalist AI Training Data Collection

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Frequently Asked Questions

How is this different from the others?

Global Access. Micro1 is more open to international applicants (outside the US/UK) than DataAnnotation or Outlier.

What is the catch?

Privacy. Micro1 projects often require you to install time-tracking software that takes screenshots of your desktop while you work to ensure you are actually working. If you are uncomfortable with monitoring software, this might not be for you.

What does the work actually look like?

It is practical, hands-on data work. You might be recording short videos, categorizing images, rating text responses, or analyzing data. The tasks are designed to be short and distinct—typically 5-60 minutes per task.

How flexible is the schedule?

Extremely. This is true "log in and work" flexibility. You can usually work for 20 minutes or 4 hours depending on your availability. There are rarely minimum hour requirements, making it ideal for side income.

Is there an interview?

Usually, no. Hiring for these roles is almost entirely based on passing an automated assessment or "qualification" task. If you pass the test, you get access to the work.

What is the interview like?

You will likely be screened by "Zara", an AI recruiter. Treat this like a real video interview—speak clearly, ensure you have good lighting, and be ready to answer technical questions verbally, as the transcript is reviewed by human managers.