Remote | Image Data Quality Review Specialist — $55–$70/hour

Key Responsibilities

Professionals in this role may contribute to:

Image Dataset Review & Validation

• Review image datasets against defined quality standards, task instructions, and evaluation rubrics
• Validate image labels, annotations, classifications, metadata, or other visual data outputs for accuracy and consistency
• Identify inconsistencies, labeling errors, edge cases, unclear examples, and recurring quality issues
• Apply structured QA criteria consistently across large volumes of image-based review tasks

Rubric-Based QA & Written Feedback

• Evaluate visual data outputs using detailed quality rubrics and documented review standards
• Provide clear written feedback explaining quality issues, patterns, and recommended corrections
• Support structured review of annotation guidelines, instruction specs, and quality criteria
• Document findings in a way that is actionable, consistent, and easy for project teams to interpret

Benchmarking & Quality Support

• Contribute to quality benchmark materials, example sets, golden samples, and review documentation
• Support evaluation workflows involving image data, visual content, annotation outputs, and vendor-style quality checks
• Help maintain strong quality standards across image review and data validation deliverables
• Work independently while maintaining accuracy, consistency, and careful attention to detail

Ideal Profile

Strong candidates may have:

• 2 years of experience in QA, editing, auditing, reviewing, annotation, data labeling, content moderation, visual review, or related quality-focused work
• Experience applying rubrics, checklists, guidelines, or structured evaluation criteria consistently
• Strong attention to detail and ability to identify subtle visual inconsistencies or quality issues
• Clear written communication skills and ability to document findings in a structured, actionable way
• Ability to work independently, manage time effectively, and follow detailed task instructions
• Comfort working with image datasets, annotation tasks, visual content, or data quality workflows

Educational Background

• A degree or professional background in data annotation, quality assurance, digital media, visual communication, design, information science, communications, editing, or a related field is helpful
• Equivalent practical experience in QA review, image annotation, visual content review, auditing, editing, or structured evaluation work is also highly relevant

Nice to Have

• Experience with AI data annotation, model evaluation, image QA, computer vision data review, or dataset validation
• Familiarity with image labeling guidelines, annotation platforms, golden sample review, or quality benchmark workflows
• Experience reviewing vendor-submitted data, structured content outputs, visual datasets, or annotation quality reports
• Strong ability to apply detailed quality standards consistently and objectively
• Comfort providing concise, high-quality written feedback on visual or data-related issues

Why This Opportunity

• Apply image review and QA expertise to structured remote project work
• Contribute to high-quality image dataset validation, annotation review, and data quality workflows
• Work on flexible, project-based assignments aligned with your review and quality assurance background
• Use your visual judgment in a focused, detail-oriented work environment
• Remote structure with competitive hourly compensation

Contract Details

• Independent contractor role
• Fully remote with flexible scheduling
• Part-time commitment depending on project availability
• Competitive rates between $55--$70 per hour depending on expertise
• Weekly payments via Stripe or Wise
• Projects may be extended, shortened, or adjusted depending on scope and performance
• Work will not involve access to confidential or proprietary information from any employer, client, or institution

About The Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

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