Bilingual AI Response Evaluator

AI Trainer Jobs; United States; Remote; USD 34,000 - 55,000; Full time

Job summary

AI Trainer Jobs is seeking a Bilingual AI Response Evaluator for a remote, contract-based role. You will review bilingual prompts and responses, compare outputs, and provide structured feedback that guides model retraining.

This position emphasizes careful judgment, clear written rationales, and consistent rubric application. You'll work asynchronously for at least 10 hours per week, with hourly compensation to be confirmed after interviews.

Qualifications

• Experience with bilingual AI evaluation or related content review.
• Ability to apply rubrics consistently across long batches.
• Provide clear written reasoning naming the rubric clause.
• Experience with inter-rater reliability and calibration cycles.
• Availability of at least 10 hours per week, asynchronously.

Responsibilities

• Evaluate bilingual AI response outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger one with a written rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and escalate to the program team for rubric updates.
• Maintain reviewer-quality scores by calibrating against gold-standard examples weekly.

Skills

Bilingual AI Response Evaluation

Written Rationale

Attention to Detail

Inter-rater Calibration

Async Availability

Job description

About the role

Bilingual AI Response Evaluator is a remote evaluation track for reviewing bilingual ai response 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 bilingual ai response 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 bilingual ai response evaluation model outputs against a versioned rubric and assign severity tags for Bilingual AI Response 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.
• Maintain reviewer-quality scores by calibrating against gold-standard examples each week.

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 bilingual ai response evaluation or adjacent content for Bilingual AI Response 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 bilingual ai response 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
• Bilingual AI Response evaluation
• Voice, language and multimodal
• AI evaluation
• Rubric writing
• Expert review