Bilingual Indonesian AI Evaluation Specialist

AI Trainer Jobs; United States; Remote; USD 28,000 - 48,000; Full time

Job summary

AuraOne is seeking a Bilingual Indonesian AI Evaluation Specialist to remotely review Indonesian prompts and outputs against a quality rubric. You will compare paired outputs, tag edge cases, and generate structured feedback for retraining the model.

Responsibilities include evaluating model outputs, labeling issues, and documenting rationales to support consistent rubric application across batches. This is a contractor, remote role with US-eligibility.

Qualifications

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

Responsibilities

• Evaluate Indonesian generalist evaluation model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select 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 for rubric updates.

Skills

Indonesian generalist evaluation

Rubric-based annotation

Inter-rater calibration

Severity tagging

Quality feedback

Job description

Bilingual Indonesian AI Evaluation Specialist is a remote evaluation track for reviewing indonesian 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.

Category: Frontier Model Evaluation · Pay: Hourly rate confirmed after the interview process · Location: Remote — US-eligible · Contractor

Bilingual Indonesian AI Evaluation Specialist is a remote evaluation track for reviewing indonesian generalist evaluation prompts and responses against AuraOne's quality rubric.

About the role

Bilingual Indonesian AI Evaluation Specialist is a remote evaluation track for reviewing indonesian 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 indonesian generalist 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 indonesian generalist evaluation model outputs against a versioned rubric and assign severity tags for Bilingual Indonesian AI Evaluation Specialist 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 indonesian generalist evaluation or adjacent content for Bilingual Indonesian AI Evaluation Specialist 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 indonesian 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

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
• Indonesian generalist evaluation