Remote Reward Hacking Data Reviewer & Rubric Auditor

AuraOne, Inc.

United States

Remote

USD 34,000 - 55,000

Full time

14 days+
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Job summary

AuraOne, Inc. is seeking a Reward Hacking Detection Preference Data Reviewer to remotely review prompts and responses against AuraOne's quality rubric. You will compare paired outputs, label edge cases, and provide structured feedback the modeling team can use to retrain.

As part of AI data review, you will label hallucinations and unsafe content, capture ambiguous prompts, and calibrate against gold-standard examples weekly. Reliable async availability (10+ hours) is required.

Qualifications

  • Prior evaluation, annotation, or human-rater experience on reward hacking detection preference data evaluation 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 itself is the problem.
  • Reliable async availability for at least 10 hours per week.

Responsibilities

  • Evaluate reward hacking detection preference data evaluation model outputs against a versioned rubric and assign severity tags for Reward Hacking Detection Preference Data Reviewer 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
Reward Hacking Detection Preference  "
Preference ranking
RLHF
Rater calibration
Reward
Hacking
Detection

Job description

AuraOne, Inc. is seeking a Reward Hacking Detection Preference Data Reviewer to remotely review prompts and responses against AuraOne's quality rubric. You will compare paired outputs, label edge cases, and provide structured feedback the modeling team can use to retrain.

As part of AI data review, you will label hallucinations and unsafe content, capture ambiguous prompts, and calibrate against gold-standard examples weekly. Reliable async availability (10+ hours) is required.

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