Video Game Annotator

AI Trainer Jobs; United States; Remote; USD 22,000 - 23,000; Full time

Job summary

AuraOne is seeking a Video Game Annotator to remotely evaluate prompts and responses against AuraOne’s quality rubric. You will compare outputs, label edge cases, and provide structured feedback to help retrain models. This contractor role offers $16–$17 per hour with flexible async hours and remote work across the US.

Responsibilities include evaluating model outputs, tagging content issues, and calibrating against rubrics weekly to sustain reviewer quality across batches.

Qualifications

• Prior evaluation, annotation, or human-rater experience on video game annotator 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 video game annotator evaluation model outputs against a versioned rubric and assign severity tags for Video Game Annotator 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

Annotation experience

Attention to detail

Clear reasoning

Async availability

Job description

Video Game Annotator is a remote evaluation track for reviewing video game annotator 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.

Category: Video, Vision & Spatial AI · Pay: $16–$17 / hr · Location: Remote — US-eligible · Contractor

Video Game Annotator is a remote evaluation track for reviewing video game annotator evaluation prompts and responses against AuraOne's quality rubric.

Role details

About the role

Video Game Annotator is a remote evaluation track for reviewing video game annotator 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.
AI data reviewers help turn video game annotator evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.
Review image and video output. Judge spatial reasoning and scene understanding.

Responsibilities

• Evaluate video game annotator evaluation model outputs against a versioned rubric and assign severity tags for Video Game Annotator 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.

What you should bring

• Prior evaluation, annotation, or human-rater experience on video game annotator evaluation or adjacent content for Video Game Annotator 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.

Role signals

Example tasks

• Compare two video game annotator 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.

Useful experience

• 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.

Compensation and schedule

$16–$17 / hr
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• Video Game Annotator evaluation

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

• The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.
• 01 Confirm profile and eligibility details.
• 02 Attach this role deliberately.
• 03 Receive a human review decision or follow-up.
• Placement timing depends on program demand and reviewer confirmation.