Remote Benchmark Ontology QA Evaluator

AuraOne, Inc.; United States; Remote; USD 30,000 - 55,000; Full time

Job summary

AuraOne's Benchmark Dataset Ontology QA Reviewer role is a remote contractor position focused on auditing and labeling model outputs. You will compare responses to a versioned rubric, assign severity tags, and provide reasoning to support selection of the strongest answer.

Ideal candidates bring experience in evaluation/annotation, clear written reasoning, and strong attention to detail. The role is remote for US-based contractors with flexible hours and weekly calibration tasks.

Qualifications

• Prior evaluation, annotation, or human-rater experience on benchmark dataset ontology QA 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 benchmark dataset ontology qa evaluation model outputs against a versioned rubric and assign severity tags for Benchmark Dataset Ontology QA 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

Benchmark Dataset Ontology QA

Data quality

Taxonomy design

Ontology review

Benchmark

Dataset

Job description

AuraOne's Benchmark Dataset Ontology QA Reviewer role is a remote contractor position focused on auditing and labeling model outputs. You will compare responses to a versioned rubric, assign severity tags, and provide reasoning to support selection of the strongest answer.

Ideal candidates bring experience in evaluation/annotation, clear written reasoning, and strong attention to detail. The role is remote for US-based contractors with flexible hours and weekly calibration tasks.