News Credibility AI Evaluator

AI Trainer Jobs; United States; Remote; USD 30,000 - 47,000; Part time

Job summary

AuraOne is seeking a News Credibility AI Evaluator to remotely review evaluation prompts and responses against our quality rubric. You will turn outputs into auditable labels, rationales, and regression cases for human data workflows.

Responsibilities include evaluating model outputs, tagging errors, calibrating scores, and flagging prompts for rubric updates, with a flexible contractor schedule.

Qualifications

• Prior evaluation, annotation, or human-rater experience on news credibility AI evaluation.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and the rubric clause.
• 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 outputs against a versioned rubric and assign severity tags.
• Compare paired responses and provide a rationale for the stronger answer.
• Label hallucinations, instruction-following failures, and unsafe content with tags.
• Capture ambiguous prompts and route to program team for rubric updates.
• Calibrate reviewer-quality scores against gold-standard examples weekly.

Skills

Evaluation experience

Annotation

Human rater

Rubric calibration

Attention to detail

Async availability

Job description

News Credibility AI Evaluator is a remote evaluation track for reviewing news credibility ai evaluation prompts and responses against AuraOne's quality rubric.

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

News Credibility AI Evaluator is a remote evaluation track for reviewing news credibility ai evaluation prompts and responses against AuraOne's quality rubric.

About the role

News Credibility AI Evaluator is a remote evaluation track for reviewing news credibility ai evaluation prompts and responses against AuraOne's quality rubric.

AI data reviewers help turn news credibility ai 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 news credibility ai evaluation model outputs against a versioned rubric and assign severity tags for News Credibility AI 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 news credibility ai evaluation or adjacent content for News Credibility AI 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.

Example tasks

• Compare two news credibility ai 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
• News Credibility AI evaluation
• Localization review
• Cultural context
• Language evaluation
• News
• Credibility