Remote Memory Evaluation Quality Reviewer

AuraOne; United States; On-site; USD 34,440 - 61,992; Full time

Job summary

AuraOne is seeking a Memory Evaluation Failure Analysis Reviewer to remotely evaluate model prompts and responses against our quality rubric. You will compare paired outputs, label edge cases, and provide structured feedback to help retrain the system.

In this contractor role you will label hallucinations, instruction-following failures, and unsafe content, capture ambiguous prompts, and calibrate reviewer quality against gold-standard examples weekly.

Qualifications

• Prior evaluation, annotation, or human-rater experience on memory evaluation failure analysis evaluation or adjacent content for Memory Evaluation Failure Analysis Reviewer 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.

Responsibilities

• Evaluate memory evaluation failure analysis evaluation model outputs against a versioned rubric and assign severity tags for Memory Evaluation Failure Analysis 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

Memory Evaluation Failure Analysis 0

Frontier evaluation

Rubric calibration

Failure analysis

Memory

Evaluation

Job description

AuraOne is seeking a Memory Evaluation Failure Analysis Reviewer to remotely evaluate model prompts and responses against our quality rubric. You will compare paired outputs, label edge cases, and provide structured feedback to help retrain the system.

In this contractor role you will label hallucinations, instruction-following failures, and unsafe content, capture ambiguous prompts, and calibrate reviewer quality against gold-standard examples weekly.