Data Annotation Specialist, Physical AI

Genesis; San Francisco (CA); On-site; USD 28,000 - 50,000; Full time

Job summary

Genesis AI is scaling its labeling team in San Francisco. You will review and annotate robot and video data that trains and evaluates our models, working side by side with the researchers who use it.

Your judgments on hard cases will shape our guidelines, our tools and, ultimately, how our robots behave.

Qualifications

• 2-5+ years of data annotation or labeling experience in a detail-heavy, deadline-driven environment.
• Strong ownership: you see work through to the finish line.
• Drive and urgency: you’re hungry to learn, move fast, and keep going on tight deadlines.
• Track record of high-accuracy work at volume while maintaining quality as speed increases.
• Sharp attention to detail and the judgment to spot when instructions fall short.
• Excellent written communication and the confidence to raise problems early.
• Comfort with ambiguity and shifting priorities in a fast-moving startup.
• Curiosity, coach-ability, and consistency.

Responsibilities

• Annotate robot episodes, videos, images, and sensor data using internal labeling tools.
• Label objects, actions, task steps, and successes or failures in robot demonstrations.
• Write clear, consistent natural-language descriptions of robot and human behavior.
• Flag ambiguous or edge cases and help define how they should be handled.
• Perform quality assurance checks on teammates' annotations and join regular calibration sessions.
• Meet quality and throughput targets while tracking your own accuracy over time.
• Report tool bugs, workflow friction, and guideline gaps to the engineering team.

Skills

Data annotation

Attention to detail

Written communication

Ownership

Drive and urgency

Meeting deadlines

Adaptability

Curiosity

Job description

About Genesis AI

Genesis AI is building a universal robotics foundation model — the "brain" that lets robots see, reason and handle objects in the real world. Our models learn from large volumes of robot, simulation and human-demonstration data, and the quality of that data directly shapes how well our robots perform.

The role

We\'re scaling our labeling team. You\'ll review and annotate robot and video data that trains and evaluates our models, working side by side with the researchers who use it. Your judgment on hard cases will shape our guidelines, our tools and, ultimately, how our robots behave.

What you\'ll do

• Annotate robot episodes, videos, images, and sensor data using internal labeling tools
• Label objects, actions, task steps, and successes or failures in robot demonstrations
• Write clear, consistent natural-language descriptions of robot and human behavior
• Flag ambiguous or edge cases and help define how they should be handled
• Perform quality assurance checks on teammates\' annotations and join regular calibration sessions
• Meet quality and throughput targets while tracking your own accuracy over time
• Report tool bugs, workflow friction, and guideline gaps to the engineering team

What we\'re looking for

• 2-5+ years of data annotation or labeling experience in a detail-heavy, deadline-driven environment
• A strong sense of ownership: you see work through to the finish line
• Drive and urgency: you\'re hungry to learn, move fast, and keep going on tight deadlines
• A track record of high-accuracy work at volume, with the ability to hold quality while speed increases
• Sharp attention to detail and the judgment to spot when instructions fall short
• Excellent written communication, and the confidence to raise problems early
• Comfort with ambiguity and shifting priorities in a fast-moving startup
• Curiosity, coach-ability, and consistency

Bonus Qualifications

• Prior data annotation, quality assurance, or issue triage experience

Experience with video, 3D, point-cloud, text, or robotics data

• Interest in robotics, machine learning, or how physical tasks are performed

Genesis AI is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, gender identity, age, disability or veteran status. Pay range reflects the expected hourly rate for this role in the San Francisco Bay Area; final rate depends on skills and experience.