Data-Video Generalist

AuraOne, Inc.; United States; Remote; USD 28,000 - 55,000; Part time

Job summary

AuraOne, Inc. seeks a Data-Video Generalist reviewer to evaluate model outputs against our quality rubric. You will label edge cases, provide rationales, and help generate regression cases for our data-human-in-the-loop workflow.

The role is remote for US-eligible contractors. You will compare paired responses, annotate with severity tags, and document recurring failure modes to guide future rubrics and training runs. Strong written reasoning and async availability are required.

Qualifications

• Prior evaluation, annotation, or human-rater experience on data video generalist evaluation.
• Clear written reasoning naming the issue and rubric clause.
• Strong attention to detail and ability to flag prompts as problems.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate data video generalist evaluation model outputs against a rubric and assign severity tags.
• Compare paired responses and select the stronger answer with written rationale.
• Label hallucinations, instruction-following failures, and unsafe content with tags.
• Capture ambiguous prompts and route to the program team for rubric updates.
• Calibrate reviewer quality against gold-standard examples each week.
• Document recurring failure modes for future training runs.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Data Video Generalist evaluation

Design

Job description

Data-Video Generalist is a remote evaluation track for reviewing data video 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.

Why this role matters

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

Responsibilities

• Evaluate data video generalist evaluation model outputs against a versioned rubric and assign severity tags for Data-Video 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.
• 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 data video generalist evaluation or adjacent content for Data-Video 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.

Example tasks

• Compare two data video 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.

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
• Data Video Generalist evaluation
• Design

Work model

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

Compensation

Hourly rate confirmed after the interview process.