Image Caption Review - English Generalist

AuraOne; United States; Remote; USD 34,000 - 49,000; Full time

Benefits offered by this job

Remote contractor role

Independent contractor

Job summary

AI Trainer Jobs is seeking a remote contractor for image caption review – English Generalist tasks. You will compare model outputs, apply a rubric, and label content with structured tags. The role requires writing clear rationales and maintaining consistency across batches.

Expected to work at least 10 hours per week with asynchronous schedule. Compensation is $30 per hour, with placement dependent on current program demand and reviewer confirmation.

Qualifications

• Prior evaluation, annotation, or human-rater experience on image caption review english generalist evaluation or adjacent content.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and rubric clause.
• Strong attention to detail and the ability to flag problematic prompts.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate image caption review outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label hallucinations, instruction-following failures, and unsafe content with tags.
• Capture ambiguous prompts and route them to the program team for rubric updates.

Skills

Evaluation experience

Attention to detail

Clear written reasoning

Async availability

Job description

About the role

Image Caption Review - English Generalist is a remote evaluation track for reviewing image caption review english 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 image caption review english 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 image caption review english generalist evaluation model outputs against a versioned rubric and assign severity tags for Image Caption Review - English 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.

Role details

Track Evaluation & annotation Work model Remote · Independent specialist contractor Compensation $30 / hr Eligible from US

What you should bring

• Prior evaluation, annotation, or human-rater experience on image caption review english generalist evaluation or adjacent content for Image Caption Review - English 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 image caption review english 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

$30 / 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