Annotation Guideline Data Specialist

AI Trainer Jobs; United States; Remote; USD 34,000 - 55,000; Full time

Job summary

AI Trainer Jobs is seeking an Annotation Guideline Data Specialist for a remote evaluation track. You will review annotation guideline data evaluation prompts and responses against AuraOne's quality rubric, compare outputs, label edge cases, and provide structured feedback for retraining.

The role is remote, US-eligible, contractor, hourly pay to be confirmed after the interview. You will help turn evaluation outputs into auditable labels, rationales, and regression cases for the modeling team,

Qualifications

• Prior evaluation, annotation, or human-rater experience on annotation guideline data evaluation.
• 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.
• Experience with inter-rater agreement metrics and calibration cycles.
• Background in linguistics, content moderation, or trust & safety review.

Responsibilities

• Evaluate annotation guideline data evaluation model outputs against a versioned rubric and assign severity tags for Annotation Guideline Data Specialist 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.

Skills

Annotation evaluation

Written reasoning

Attention to detail

Availability

Rubric application

Linguistics background

Inter-rater metrics

Job description

Annotation Guideline Data Specialist is a remote evaluation track for reviewing annotation guideline data 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.

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

Annotation Guideline Data Specialist is a remote evaluation track for reviewing annotation guideline data evaluation prompts and responses against AuraOne's quality rubric.

About the role

Annotation Guideline Data Specialist is a remote evaluation track for reviewing annotation guideline data 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 annotation guideline data 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 annotation guideline data evaluation model outputs against a versioned rubric and assign severity tags for Annotation Guideline Data Specialist 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 annotation guideline data evaluation or adjacent content for Annotation Guideline Data Specialist 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 annotation guideline data evaluation model responses to the same prompt and pick the stronger one with rationale.
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• 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
• Annotation Guideline Data evaluation
• Data quality
• Taxonomy design
• Ontology review
• Annotation
• Guideline

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.