Visual Content Evaluator (AI Image Quality)

You will review original images alongside AI-generated versions to assess visual accuracy and quality. You will record clear, useful feedback that helps improve image-generation systems.

• Upload original images that meet the project specifications.
• Compare original and AI-generated images side by side.
• Review lighting, perspective, texture, anatomy, color, shadows, patterns, surfaces, and text.
• Flag issues such as warped hands, smudged surfaces, inconsistent shadows, broken patterns, and misshapen text.
• Describe each issue clearly and concisely, including its exact location in the image.
• Apply detailed quality guidelines consistently and prioritize accurate, actionable feedback.

What it pays and takes

This is a part-time contractor role for candidates in the United States.

• Pay: $40 to $60 per hour.
• Location: Open to candidates in the United States.
• Language: Fluent written and verbal English, including the ability to produce error-free image notes.
• Strong visual acuity and the ability to notice subtle differences between similar images.
• Careful, reliable judgment when following detailed review standards.
• Understanding of AI-generated image failure modes and visual quality concerns.
• Helpful experience includes photography, digital imaging, graphic design, photo editing, image evaluation, data annotation, image comparison, or visual quality assurance.
• Familiarity with technical terms for describing visual defects is helpful.

How it works

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 3 screening questions.

About AI training work

AI training is the human work behind systems that learn from examples, including reviewing images and rating model outputs. Careful visual reviewers help models produce more accurate and consistent results.