Multimodal Game Theory

AuraOne, Inc.; United States; Remote; USD 45,000 - 65,000; Full time

Job summary

AuraOne, Inc. invites a meticulous remote reviewer to join its Multimodal Game Theory evaluation track. You will assess model outputs against a versioned rubric, label edge cases, and provide structured feedback for retraining the modeling team.

This contractor role requires clear written reasoning, attention to detail, and the ability to calibrate scores against gold-standard examples weekly. You must be authorized to work from the United States and able to commit at least 10 hours per week.

Qualifications

• Experience in evaluation or annotation of multimodal content.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning naming the issue and rubric clause.
• Attention to detail and ability to flag prompt problems.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate model outputs against rubric and assign severity tags.
• Compare paired responses and justify the stronger answer.
• Tag unsafe content with proper policy category.
• Document recurring failure modes for rubric updates.
• Calibrate reviewer scores against gold-standard examples weekly.

Skills

Model output evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

Multimodal Game Theory evaluation

Job description

Multimodal Game Theory is a remote evaluation track for reviewing multimodal game theory 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.

Why this role matters

AI data reviewers help turn multimodal game theory evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.

Responsibilities

• Evaluate multimodal game theory evaluation model outputs against a versioned rubric and assign severity tags for Multimodal Game Theory 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.

Qualifications

• Prior evaluation, annotation, or human-rater experience on multimodal game theory evaluation or adjacent content for Multimodal Game Theory 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.

Example tasks

• Compare two multimodal game theory evaluation model responses to the same prompt and pick the stronger one with rationale.
• 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.

Nice to have

• 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.

Skills

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• Multimodal Game Theory evaluation

Work model

Remote — US-eligible. Remote · Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

$40 / hr

Prior evaluation, annotation, or human-rater experience on multimodal game theory evaluation or adjacent content for Multimodal Game Theory 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.