Video Evaluation Generalist

AI Trainer Jobs; United States; Remote; USD 21,000 - 28,000; Full time

Job summary

AI Trainer Jobs is seeking a Video Evaluation Generalist for a remote role that reviews prompts and responses against AuraOne's quality rubric. You will compare paired outputs, label edge cases, and provide structured feedback for retraining efforts.

Responsibilities include evaluating model outputs, tagging issues, and calibrating with gold standards. The role requires reliable part-time availability and attention to detail in a remote setting.

Qualifications

• Experience evaluating or annotating video content is preferred.
• Ability to apply structured rubrics and provide clear reasoning.

Responsibilities

• Evaluate model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label hallucinations, policy violations and safety issues with tags.
• Capture ambiguous prompts and suggest rubric updates.
• Maintain calibration against gold-standard examples weekly.

Skills

Video evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Model output evaluation

Job description

Video Evaluation Generalist is a remote evaluation track for reviewing video evaluation generalist 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.

Category: Video, Vision & Spatial AI · Pay: $15–$20 / hr · Location: Remote — US-eligible · Contractor

Video Evaluation Generalist is a remote evaluation track for reviewing video evaluation generalist evaluation prompts and responses against AuraOne's quality rubric.

Role details

About the role

Video Evaluation Generalist is a remote evaluation track for reviewing video evaluation generalist 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 evaluation generalist 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 evaluation generalist evaluation model outputs against a versioned rubric and assign severity tags for Video Evaluation Generalist 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 evaluation generalist evaluation or adjacent content for Video Evaluation Generalist 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 evaluation generalist 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

$15–$20 / hr
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 Evaluation Generalist evaluation

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.
- 01 Confirm profile and eligibility details.
- 02 Attach this role deliberately.
- 03 Receive a human review decision or follow-up.
Placement timing depends on program demand and reviewer confirmation.