Remote AI Data Evaluation & Annotation Expert

AI Trainer Jobs; United States; Remote; USD 34,000 - 62,000; Part time

Job summary

AuraOne is seeking an AI Data Annotation Expert for a remote evaluation track. You will review prompts and responses against a versioned rubric, provide structured feedback, and help turn outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.

You will compare paired outputs and tag issues to support model improvement. Applicants should have prior evaluation or annotation experience, the ability to apply rubrics consistently, and strong written reasoning with

Qualifications

• Prior evaluation, annotation, or human-rater experience on ai data annotation 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 ai data annotation evaluation model outputs against a versioned rubric and assign severity tags for AI Data Annotation Expert 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.

Skills

Model output evaluation

Rubric-based annotation

Inter-rater calibration

Attention to detail

Job description

AuraOne is seeking an AI Data Annotation Expert for a remote evaluation track. You will review prompts and responses against a versioned rubric, provide structured feedback, and help turn outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.

You will compare paired outputs and tag issues to support model improvement. Applicants should have prior evaluation or annotation experience, the ability to apply rubrics consistently, and strong written reasoning with