Remote Punjabi Transcription Evaluator & AI Quality

AuraOne, Inc.; United States; Remote; USD 28,000 - 52,000; Full time

Job summary

Punjabi Transcription Expert — Audio AI Evaluation (Remote) is a remote evaluation track for reviewing punjabi transcription 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 punjabi transcription evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.

Qualifications

• Prior evaluation, annotation, or human-rater experience on punjabi transcription evaluation or adjacent content for Punjabi Transcription Expert — Audio AI Evaluation (Remote) 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.

Responsibilities

• Evaluate punjabi transcription evaluation model outputs against a versioned rubric and assign severity tags for Punjabi Transcription Expert — Audio AI Evaluation (Remote) 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.
• Document recurring failure modes so the modeling team can target them in the next training run.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Punjabi Transcription evaluation

Job description

Punjabi Transcription Expert — Audio AI Evaluation (Remote) is a remote evaluation track for reviewing punjabi transcription 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 punjabi transcription evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.