Remote Video Annotation Quality Analyst

AuraOne; United States; Remote; USD 34,000 - 62,000; Full time

Job summary

AuraOne is seeking a Video Annotation Specialist - Post-Production Review for a remote contractor role. You will evaluate model outputs against a rubric, label edge cases, and provide structured feedback to help retrain the system.

Responsibilities include comparing paired responses, tagging unsafe content, and documenting failure modes for model improvements. Requires clear rationale and attention to detail with weekly calibration against gold standards.

Qualifications

• Prior evaluation, annotation, or human-rater experience on video annotation evaluation or adjacent content.
• 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.
• Comfort applying multi-page rubrics consistently across long batches.

Responsibilities

• Evaluate video annotation evaluation model outputs against a versioned rubric and assign severity tags for Video Annotation Specialist - Post-Production Review (Remote) 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

Video Annotation evaluation

Design

Job description

AuraOne is seeking a Video Annotation Specialist - Post-Production Review for a remote contractor role. You will evaluate model outputs against a rubric, label edge cases, and provide structured feedback to help retrain the system.

Responsibilities include comparing paired responses, tagging unsafe content, and documenting failure modes for model improvements. Requires clear rationale and attention to detail with weekly calibration against gold standards.