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AI Video Annotator - Post-Production Quality Review

AuraOne Human Data
Remote

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Job Details

$15 - $20 an hour
13 hours ago

Qualifications

Software issue identification
Writing skills
Bug Reporting (Quality assurance practices)
Mid-level
Quality control audit
Linguistics
Quality performance measurement
Metadata tagging
Document quality checks
Model evaluation
Rubric-based test scoring
Content review
Linguistics

Full Job Description

AI Video Annotator - Post-Production Quality Review is a remote evaluation track for reviewing ai video annotator 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.

Why this role matters

AI data reviewers help turn ai video annotator evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.

Responsibilities

Evaluate ai video annotator evaluation model outputs against a versioned rubric and assign severity tags for AI Video Annotator - Post-Production Quality Review 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.

Qualifications

Prior evaluation, annotation, or human-rater experience on ai video annotator evaluation or adjacent content for AI Video Annotator - Post-Production Quality Review 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.

Example tasks

Compare two ai video annotator 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.

Nice to have

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.

Skills

Model output evaluation
Rubric-based annotation
Severity tagging
Inter-rater calibration
AI Video Annotator evaluation

Work model

Remote — US-eligible. Remote · Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

$15–$20 / hr

Application process

Apply through AuraOne's specialist intake for role-specific routing and review. Final project scope, schedule, and contractor terms are confirmed before placement.

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