Human Resources Operations AI Evaluator

AI Trainer Jobs; United States; Remote; USD 28,000 - 55,000; Part time

Job summary

AI Trainer Jobs is seeking a remote Human Resources Operations AI Evaluator contractor to review evaluation prompts and model outputs against a versioned rubric. You will label edge cases, provide structured feedback, and help retrain the modeling team.

Responsibilities include comparing responses, selecting stronger answers with reasoning, tagging content per policy, and flagging prompts for rubric updates. Requires strong attention to detail and reliable async availability for 10+ hours weekly.

Qualifications

• Prior evaluation, annotation, or human-rater experience in HR AI evaluation.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning naming the issue and rubric clause.
• Strong attention to detail and flag prompts when necessary.
• Reliable async availability for at least 10 hours per week.
• Background in linguistics, content moderation, or trust & safety review.
• Familiarity with inter-rater agreement metrics.
• Domain expertise to spot errors automated checks miss.

Responsibilities

• Evaluate model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label hallucinations, instruction-following failures, and unsafe content with tags.
• Capture ambiguous prompts and route to program team for rubric updates.
• Audit batches for rubric consistency and report drift.

Skills

Evaluation experience

Rubric application

Written reasoning

Attention to detail

Async availability

Linguistics background

Inter-rater metrics

Domain expertise

Job description

About the role

Human Resources Operations AI Evaluator is a remote evaluation track for reviewing human resources operations ai 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 human resources operations 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 human resources operations ai evaluation model outputs against a versioned rubric and assign severity tags for Human Resources Operations 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.

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 human resources operations ai evaluation or adjacent content for Human Resources Operations 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.

Role signals

Example tasks

• Compare two human resources operations 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
• Human Resources Operations AI evaluation
• Enterprise operations
• AI evaluation
• Rubric writing
• Expert review

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.

• 01 Confirm profile and eligibility details.
• 02 Attach this role deliberately.
• 03 Receive a human review decision or follow-up.
  Placement timing depends on program demand and reviewer confirmation.