Robotics Data Labeler — High-Impact AI Training Data

Genesis; San Carlos (CA); On-site; USD 30,000 - 48,000; Full time

Job summary

Genesis AI is scaling its labeling team in the San Francisco Bay Area. You will review and annotate robot and video data that trains and evaluates our models, collaborating closely with researchers who use the data.

Your judgments on difficult cases will help shape guidelines, tools, and how our robots behave. We seek candidates with 2–5+ years of data annotation experience, a strong sense of ownership, and the drive to learn quickly under tight deadlines.

Qualifications

• 2-5+ years of data annotation experience in a detail-heavy, deadline-driven environment.
• Strong sense of ownership and follow-through.
• Drive and urgency to learn, move fast, and meet tight deadlines.
• Track record of high-accuracy work at volume while maintaining quality as speed increases.
• Sharp attention to detail and judgment to flag gaps in instructions.
• Excellent written communication and ability to raise problems early.
• Comfort with ambiguity and shifting priorities in a fast-moving startup.

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

Detail-oriented

Ownership

Fast learner

Written communication

Ambiguity tolerance

Consistency

Job description

Genesis AI is scaling its labeling team in the San Francisco Bay Area. You will review and annotate robot and video data that trains and evaluates our models, collaborating closely with researchers who use the data.

Your judgments on difficult cases will help shape guidelines, tools, and how our robots behave. We seek candidates with 2–5+ years of data annotation experience, a strong sense of ownership, and the drive to learn quickly under tight deadlines.