Remote Robot Trajectory Evaluation Specialist

AuraOne; United States; On-site; USD 55,104 - 82,656; Full time

Job summary

AuraOne seeks a remote Contractor to review robot trajectory task evaluation prompts and responses, applying a versioned rubric and producing auditable labels and rationales for retraining.

You will compare paired outputs, label edge cases, and help calibrate reviewer-quality scores against gold-standard examples weekly. Prior evaluation experience and meticulous reasoning are essential.

Qualifications

• Prior evaluation, annotation, or human-rater experience on robot trajectory task evaluation or adjacent content for Robot Trajectory Task Evaluator work.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and the rubric clause being applied.
• Strong attention to detail and the ability to flag when a prompt itself is the problem.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate robot trajectory task evaluation model outputs against a versioned rubric and assign severity tags for Robot Trajectory Task Evaluator assignments.
• Compare paired responses and pick the stronger answer with a written rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route them back to the program team for rubric updates.
• Maintain reviewer-quality scores by calibrating against gold-standard examples each week.
• Document recurring failure modes so the modeling team can target them in the next training run.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Robot Trajectory Task evaluation

Robotics evaluation

Embodied AI

Safety review

Robot

Trajectory

Job description

AuraOne seeks a remote Contractor to review robot trajectory task evaluation prompts and responses, applying a versioned rubric and producing auditable labels and rationales for retraining.

You will compare paired outputs, label edge cases, and help calibrate reviewer-quality scores against gold-standard examples weekly. Prior evaluation experience and meticulous reasoning are essential.