Bilingual Document Annotator

AI Trainer Jobs; United States; Remote; USD 34,000 - 41,000; Full time

Job summary

AI Trainer Jobs is seeking a Bilingual Document Annotator for a remote contractor position to review document annotation prompts and responses against AuraOne's quality rubric. You will compare outputs, label edge cases, and provide structured feedback the modeling team can use to retrain.

Ideal candidates have prior evaluation or annotation experience, strong written reasoning to name issues, and the ability to apply rubrics consistently across multi-page tasks.

Qualifications

• Prior evaluation, annotation, or human-rater experience on document annotation or adjacent content.
• Clear written reasoning that names the issue and the rubric clause being applied.
• Reliable async availability for at least 10 hours per week.
• Ability to apply multi-page rubrics consistently across long batches.

Responsibilities

• Evaluate document annotation model outputs against a versioned rubric and assign severity tags for Bilingual Document Annotator 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.

Skills

Linguistics background

Content moderation experience

Inter-rater calibration

Attention to detail

Clear written reasoning

Async availability

Annotation experience

Tools

JSON

PDF Analysis

Rubric systems

Job description

Bilingual Document Annotator is a remote evaluation track for reviewing document annotation 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: $25–$30 / hr · Location: Remote — US-eligible · Contractor

Bilingual Document Annotator is a remote evaluation track for reviewing document annotation prompts and responses against AuraOne's quality rubric.

Role details

About the role

Bilingual Document Annotator is a remote evaluation track for reviewing document annotation 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 document annotation 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 document annotation model outputs against a versioned rubric and assign severity tags for Bilingual Document Annotator 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 document annotation or adjacent content for Bilingual Document Annotator 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 document annotation 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

$25–$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
• Document annotation
• Attention to Detail
• Data Validation
• Error Detection
• JSON
• Languages
• PDF Analysis