Robotics Data Labeling Specialist

Carrerlift; San Francisco (CA); On-site; USD 30,000 - 52,000; Full time

Job summary

Genesis AI is expanding its labeling team to support robotics foundation models. You will review robot and video data and work closely with researchers who use the annotations to improve labeling guidelines and internal tools. The role emphasizes delivering accurate labels at scale in a startup environment.

You will participate in QA, calibrations, and escalation of edge cases, aiming to meet defined quality and throughput goals while maintaining speed and reliability of labeling outputs.

Qualifications

• 2-5+ years of data annotation or labeling experience.
• Ownership and ability to carry tasks through to completion.
• Ability to deliver under tight timelines.
• Accurate work at high volume while maintaining quality.
• Attention to detail and clear written communication.

Responsibilities

• Annotate robot episodes, videos, images and sensor information with internal tools.
• Identify objects, actions, task stages and success/failure of demonstrations.
• Produce clear natural-language descriptions of actions.
• Escalate unclear cases and help standardize labeling rules.
• Review teammate annotations as part of QA and calibration.
• Work toward quality and throughput goals while tracking accuracy.
• Report labeling-tool bugs and workflow issues to the engineering team.

Skills

Attention to detail

Deadline-driven

Ownership

Rapid learning

Strong written communication

Startup pace adaptability

Job description

Genesis AI is expanding its labeling team to support robotics foundation models. You will review robot and video data and work closely with researchers who use the annotations to improve labeling guidelines and internal tools. The role emphasizes delivering accurate labels at scale in a startup environment.

You will participate in QA, calibrations, and escalation of edge cases, aiming to meet defined quality and throughput goals while maintaining speed and reliability of labeling outputs.