Photographer (Image Quality Evaluation)

You will support AI training by reviewing photographic content and AI-generated images. You will compare images, identify meaningful differences, and explain image-quality issues in clear written feedback.

The work calls for careful visual judgment across lighting, composition, perspective, texture, artifacts, and other details. You may also revise observations during review cycles and communicate through written and verbal discussions when clarification is needed.

• Upload original photographs through a secure digital platform.
• Compare photographs with AI-generated images.
• Identify visual flaws, artifacts, anomalies, and weaknesses in composition or perspective.
• Describe findings with accurate photographic and technical terms.
• Write clear, concise feedback and revise observations during review cycles.

This is part-time contractor work for candidates in the United States. Previous AI experience is not required, but you should be comfortable making careful, precise judgments about image quality.

• Pay: $21 to $65 per hour.
• Work type: Part-time contractor role.
• Location: Open to candidates in the United States.
• Language: Fluent written English, with accurate spelling and grammar.
• Background: Demonstrated experience in photography, digital imaging, photo editing, graphic design, or a related creative field.
• Skills: Strong visual attention to detail, a meticulous and methodical approach, and the ability to explain image-quality judgments clearly and concisely.
• Helpful experience: Image evaluation, annotation, or digital quality assurance.

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.

AI training is the human work behind systems that learn from examples prepared and reviewed by people. Image reviewers help improve these systems by judging visual content and giving precise feedback on what models produce.