Data Annotation Specialist, Physical AI

Genesis AI; San Carlos (CA); On-site; USD 42,000 - 66,000; Full time

Job summary

Genesis AI is scaling its labeling team to annotate robot and video data that trains and evaluates our universal robotics models. You will work closely with researchers, applying judgment on hard cases to shape labeling guidelines, tools, and robot behavior.

We value hands-on contributors who own their work, move quickly under deadlines, and deliver high-quality annotations with attention to detail. Join a fast-moving startup that values curiosity and collaboration.

Qualifications

• 2–5+ years of data annotation experience in a detail-heavy, deadline-driven environment.
• Strong ownership: you see work through to the finish line.
• Excellent written communication and the confidence to raise problems early.

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

Deadline-driven

Tools

Internal labeling tools

Job description

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