Video Data Reviewer

AI Trainer Jobs; United States; Remote; USD 2,066,000 - 3,444,000; Full time

Job summary

AI Trainer Jobs is seeking a remote Video Data Reviewer to evaluate model outputs against a fixed rubric and provide structured feedback. You will label edge cases, drafts rationales, and contribute to improving the rubric for future retraining.

Ideal candidates have prior video evaluation experience, excellent written reasoning, and strong attention to detail. This is a contractor role with flexible task volume and weekly calibration.

Qualifications

• Prior evaluation or annotation experience on video data evaluation.
• Ability to apply multi-page rubrics consistently.
• Clear written reasoning naming the issue and rubric clause.
• Reliable async availability for 10+ hours per week.

Responsibilities

• Evaluate video data evaluation outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label hallucinations, policy failures, and unsafe content with tags.
• Capture ambiguous prompts and route them for rubric updates.
• Calibrate reviewer quality against gold-standard examples weekly.

Skills

Video data evaluation

Annotation

Written reasoning

Attention to detail

Async availability

Job description

About the role

Video Data Reviewer is a remote evaluation track for reviewing video data evaluation prompts and responses against AuraOne's quality rubric. Reviewers compare paired outputs, label edge cases, and write the kind of structured feedback the modeling team can use to retrain.
AI data reviewers help turn video data evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.
Review image and video output. Judge spatial reasoning and scene understanding.

Responsibilities

• Evaluate video data evaluation model outputs against a versioned rubric and assign severity tags for Video Data Reviewer 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.

What you should bring

• Prior evaluation, annotation, or human-rater experience on video data evaluation or adjacent content for Video Data Reviewer 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.

Role signals

Example tasks

• Compare two video data evaluation model responses to the same prompt and pick the stronger one with rationale.
• Tag an unsafe response with the correct policy category and severity.
• Audit a 50-row batch for rubric consistency and report drift to the program lead.
• Propose a rubric clarification after spotting a recurring failure mode.

Useful experience

• Background in linguistics, content moderation, or trust & safety review.
• Experience with inter-rater agreement metrics and calibration cycles.
• Domain expertise that lets you spot subject-matter errors automated checks miss.

Compensation and schedule

Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• Video Data evaluation
• Design