Point Cloud Evaluator

AI Trainer Jobs; United States; Remote; USD 34,000 - 48,000; Part time

Job summary

AuraOne is seeking a Point Cloud Evaluator for a remote contractor role to review prompts and model outputs against our quality rubric. You will compare responses, label edge cases, and provide structured feedback to retrain the system. This is an independent contractor position with hourly compensation to be confirmed after interview.

Responsibilities include evaluating outputs, tagging issues, and calibrating against gold-standard examples weekly, with a focus on accuracy and clear rationale.

Qualifications

• Prior evaluation, annotation, or human-rater experience on point cloud evaluation or adjacent content for Point Cloud Evaluator work.
• Clear written reasoning that names the issue and the rubric clause being applied.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate point cloud evaluation model outputs against a versioned rubric and assign severity tags for Point Cloud Evaluator 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.

Skills

Evaluation experience

Attention to detail

Written reasoning

Async availability

Point cloud domain knowledge

Job description

Point Cloud Evaluator is a remote evaluation track for reviewing point cloud 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: Hourly rate confirmed after the interview process · Location: Remote — US-eligible · Contractor

Point Cloud Evaluator is a remote evaluation track for reviewing point cloud evaluation prompts and responses against AuraOne's quality rubric.

Role details

About the role

Point Cloud Evaluator is a remote evaluation track for reviewing point cloud 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 point cloud 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 point cloud evaluation model outputs against a versioned rubric and assign severity tags for Point Cloud Evaluator 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.Track Evaluation & annotation Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Prior evaluation, annotation, or human-rater experience on point cloud evaluation or adjacent content for Point Cloud Evaluator 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 point cloud 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

Hourly rate confirmed after the interview process.
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
• Point Cloud evaluation
• Computer vision
• Spatial reasoning
• Video QA
• Point
• Cloud