Robotics Data Reviewer: Safety & Trajectory Expert

AI Trainer Jobs; United States; Remote; USD 34,000 - 83,000; Full time

Job summary

AuraOne is seeking a Robotics Data Trainer for a remote review track evaluating robotics outputs against real-world physical-AI constraints. Reviewers grade trajectory choices, perception assumptions, and safety envelopes; flag failure modes; and document corrected behavior so the modeling team can train on it.

Responsibilities include reviewing outputs against safety standards, scoring perception and motion, and adjudicating cases using firm operating procedures.

Qualifications

• Hands-on experience with robotic, autonomous, or teleoperated systems.
• Ability to reason about perception, motion planning, and safety envelopes.
• Familiarity with structured incident taxonomies and severity scoring.
• Clear written explanations naming failure modes and the standards being applied.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review robotics outputs against current safety standards and operating envelopes for Robotics Data Trainer assignments.
• Grade perception, motion, and decision logic on a structured rubric.
• Flag near-miss and unsafe trajectories with severity tags that match incident taxonomies.
• Capture the corrected behavior or reference trajectory so the modeling team can train on it.
• Adjudicate disputed cases against published standards or firm operating procedures.

Skills

Robotics experience

Perception reasoning

Safety envelopes

Incident taxonomy

Written reasoning

Async availability

Job description

AuraOne is seeking a Robotics Data Trainer for a remote review track evaluating robotics outputs against real-world physical-AI constraints. Reviewers grade trajectory choices, perception assumptions, and safety envelopes; flag failure modes; and document corrected behavior so the modeling team can train on it.

Responsibilities include reviewing outputs against safety standards, scoring perception and motion, and adjudicating cases using firm operating procedures.