Computer Vision and Spatial Reasoning Evaluator

AI Trainer Jobs; United States; Remote; USD 34,000 - 55,000; Part time

Job summary

AI Trainer Jobs seeks an evaluator for a remote role focused on reviewing computer vision and spatial reasoning prompts and responses. You will compare outputs, label edge cases, and provide structured feedback to retrain the model.

Responsibilities include evaluating outputs against rubrics, tagging issues, and documenting rationales for program improvement. This is a contract, remote position with hourly compensation after interview.

Qualifications

• Prior evaluation, annotation, or human-rater experience on computer vision and spatial reasoning evaluation or adjacent content for CV and Spatial Reasoning Evaluator work.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and rubric clause being applied.
• Strong attention to detail and ability to flag prompt issues.

Responsibilities

• Evaluate model outputs against a versioned rubric and assign severity tags for CV and Spatial Reasoning Evaluator assignments.
• Compare paired responses and select 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

Model evaluation

Rubric-based annotation

Severity tagging

Inter-rater calibration

CV and Spatial Reasoning evaluation

AI evaluation

Rubric writing

Expert review

Job description

About the role

Computer Vision and Spatial Reasoning Evaluator is a remote evaluation track for reviewing computer vision and spatial reasoning 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 computer vision and spatial reasoning 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 computer vision and spatial reasoning evaluation model outputs against a versioned rubric and assign severity tags for Computer Vision and Spatial Reasoning 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.

Role details

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 computer vision and spatial reasoning evaluation or adjacent content for Computer Vision and Spatial Reasoning 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.

Role signals

Example tasks

• Compare two computer vision and spatial reasoning 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
• Computer Vision and Spatial Reasoning evaluation
• Robotics and physical AI
• AI evaluation
• Rubric writing
• Expert review

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.