Children Safety Content AI Evaluator

AI Trainer Jobs; United States; Remote; USD 34,000 - 48,000; Full time

Benefits offered by this job

Remote work

Contractor role

Job summary

AuraOne is seeking a Children Safety Content AI Evaluator for a remote, contractor-based role. You will evaluate model outputs, compare responses, and label content with structured tags according to our quality rubric.

Ideal candidates have prior evaluation/annotation experience on safety content, can clearly explain rubrics, and commit to at least 10 hours per week with reliable async availability.

Qualifications

• Prior evaluation, annotation, or human-rater experience on children safety content AI evaluation or adjacent content.
• Clear written reasoning naming the issue and the rubric clause applied.
• Strong attention to detail and ability to flag issues.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate children safety content evaluation model outputs against a rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route them for rubric updates.

Skills

Evaluation experience

Annotation

Written reasoning

Attention to detail

Async availability

Job description

Children Safety Content AI Evaluator is a remote evaluation track for reviewing children safety content ai 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: Frontier Model Evaluation · Pay: Hourly rate confirmed after the interview process · Location: Remote — US-eligible · Contractor

Children Safety Content AI Evaluator is a remote evaluation track for reviewing children safety content ai evaluation prompts and responses against AuraOne's quality rubric.

About the role

Children Safety Content AI Evaluator is a remote evaluation track for reviewing children safety content ai 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 children safety content ai evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.
Review frontier model outputs. Judge benchmark failures and calibrate other evaluators.

Responsibilities

• Evaluate children safety content ai evaluation model outputs against a versioned rubric and assign severity tags for Children Safety Content AI Evaluator 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 Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Prior evaluation, annotation, or human-rater experience on children safety content ai evaluation or adjacent content for Children Safety Content AI Evaluator 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 children safety content ai 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
• Children Safety Content AI evaluation
• Localization review
• Cultural context
• Language evaluation
• Children
• Safety
• Content