Data Annotation 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

About the role

• Genesis AI is expanding the team responsible for labeling data used to train and evaluate its robotics foundation models.
• The work involves reviewing robot and video data while collaborating closely with researchers who use the resulting annotations.
• Decisions made on difficult examples will help improve labeling guidelines, internal tools and robot behavior.

What you’ll work on

• Annotate robot episodes, videos, images and sensor information with Genesis AI’s internal labeling tools.
• Identify objects, actions, task stages and whether robot demonstrations succeeded or failed.
• Produce clear and consistent natural-language descriptions of robot and human actions.
• Escalate unclear and edge-case examples and help establish how similar cases should be labeled in the future.
• Review annotations produced by teammates as part of quality assurance and participate in recurring calibration sessions.
• Work toward defined quality and throughput goals while monitoring your own annotation accuracy.
• Report labeling-tool bugs, workflow problems and missing or unclear guidance to the engineering team.

What we’re looking for

• Candidates should have 2-5+ years of data annotation or labeling experience in work that requires close attention to detail and meeting deadlines.
• Applicants should demonstrate ownership and consistently carry assigned work through to completion.
• The role requires urgency, willingness to learn quickly and the ability to keep delivering under tight timelines.
• Candidates should have experience producing accurate work at high volume while maintaining quality as speed increases.
• Strong attention to detail, sound judgment, excellent written communication and willingness to surface problems early are expected.
• Applicants should be comfortable with ambiguity, changing priorities and the pace of a startup environment.
• Curiosity, consistency and openness to coaching are important qualities for the role.

Bonus qualifications

• Previous work in data annotation, quality assurance or issue triage is beneficial.
• Experience handling video, 3D, point-cloud, text or robotics datasets is useful.
• Interest in robotics, machine learning or understanding how physical tasks are performed is considered a plus.

About Genesis AI

• Genesis AI is developing a universal robotics foundation model intended to help robots perceive, reason and manipulate objects in real-world environments.
• Its models learn from robot, simulation and human-demonstration datasets, making data quality an important factor in model performance.
• Genesis AI states that it is an equal opportunity employer and does not discriminate based on protected characteristics including race, religion, color, national origin, sex, sexual orientation, gender identity, age, disability or veteran status.
• The company notes that its referenced pay range represents the expected hourly rate for the San Francisco Bay Area and that final compensation depends on skills and experience, although no numerical range is provided in the post.