Remote Multimodal Signals Evaluator & Feedback Analyst

AuraOne, Inc.; United States; Remote; USD 109,106,000 - 120,127,000; Part time

Job summary

AuraOne, Inc. is seeking a remote contractor to review multimodal signals evaluation prompts and responses against a versioned rubric. You will label edge cases, write structured feedback, and contribute to model retraining data for AuraOne Human Data.

Responsibilities include evaluating model outputs, selecting stronger responses with rationale, and documenting failure modes to improve future rubrics. The role requires clear reasoning and high attention to detail, with flexible async

Qualifications

• Prior evaluation, annotation, or human-rater experience on multimodal signals evaluation or adjacent content for Multimodal Signals work.
• 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 multimodal signals evaluation 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 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.
• Document recurring failure modes for targeted improvements in training.

Skills

Experience in evaluation/annotation

Attention to detail

Clear written reasoning

Async availability

Rubric-based labeling

Job description

AuraOne, Inc. is seeking a remote contractor to review multimodal signals evaluation prompts and responses against a versioned rubric. You will label edge cases, write structured feedback, and contribute to model retraining data for AuraOne Human Data.

Responsibilities include evaluating model outputs, selecting stronger responses with rationale, and documenting failure modes to improve future rubrics. The role requires clear reasoning and high attention to detail, with flexible async