Audiobook QA Expert — Dutch

AuraOne

United States

On-site

USD 21,000 - 28,000

Part time

14 days+

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Job summary

AuraOne Human Data is seeking an experienced Audiobook QA Expert — Dutch to work remotely on evaluation tasks for audio annotation prompts and model outputs. You will compare responses, label issues, and provide structured feedback to help retrain the model.

Ideal candidates have prior audio annotation or similar experience, strong written reasoning, and reliable part-time availability to fit contractor workflows. This is a remote, task-based role with flexible hours.

Qualifications

  • Prior evaluation, annotation, or human-rater experience on audio annotation or adjacent content.
  • 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 is the problem.
  • Reliable async availability for at least 10 hours per week.

Responsibilities

  • Evaluate audio annotation model outputs against a versioned rubric and assign severity tags for Audiobook QA Expert — Dutch 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

Model evaluation
Rubric annotation
Severity tagging
Inter-rater calibration
Audio annotation

Job description

About the role

Audiobook QA Expert — Dutch is a remote evaluation track for reviewing audio 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 audio 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 audio annotation model outputs against a versioned rubric and assign severity tags for Audiobook QA Expert — Dutch 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 audio annotation or adjacent content for Audiobook QA Expert — Dutch 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 audio 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

$15–$20 / 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
  • Audio annotation
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