Computer Vision Expert

AI Trainer Jobs; United States; Remote; USD 110,000 - 152,000; Part time

Job summary

AI Trainer Jobs is sourcing a Computer Vision Expert for a remote evaluation track. You will review computer vision prompts and responses against AuraOne's quality rubric, label edge cases, and provide structured feedback to retrain models.

As a contractor, you will compare paired outputs, write rationales, and tag issues such as hallucinations or instruction-following failures. A strong eye for detail and reliable weekly availability (approximately 10 hours) are essential.

Qualifications

• Prior evaluation, annotation, or human-rater experience in computer vision evaluation.
• Ability to apply multi-page rubrics consistently across large batches.
• Clear written reasoning naming issues and rubric clauses.
• Strong attention to detail and ability to flag prompt problems.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate computer vision evaluation model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route to program team for rubric updates.
• Maintain reviewer-quality scores by calibrating against gold-standard examples weekly.

Skills

Evaluation experience

Annotation experience

Attention to detail

Written reasoning

Async availability

Job description

Computer Vision Expert is a remote evaluation track for reviewing computer vision 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: $80–$110 / hr · Location: Remote — US-eligible · Contractor

Computer Vision Expert is a remote evaluation track for reviewing computer vision 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 evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.
Review image and video output. Judge spatial reasoning and scene understanding.

Role details

About the role

Computer Vision Expert is a remote evaluation track for reviewing computer vision 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 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 evaluation model outputs against a versioned rubric and assign severity tags for Computer Vision Expert 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 computer vision evaluation or adjacent content for Computer Vision Expert 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 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

$80–$110 / 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
• Computer Vision 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.