Students Across All Disciplines AI Evaluation Contributor

You will assess AI-related content for accuracy, depth, clarity, and overall quality within your academic discipline. Your work may include written, visual, and diagram-based materials.

You will explain your decisions clearly, identify errors and missing context, and complete defined annotation tasks during project windows.

• Evaluate content using knowledge from your academic field
• Write clear explanations and structured reasons for your ratings
• Find errors, ambiguity, missing context, and other quality issues
• Interpret materials such as schematics, spectra, maps, clinical images, artworks, and data charts
• Complete project-based evaluation and annotation assignments

What it pays and takes

This is remote, asynchronous, project-based work designed to fit around academic commitments. It is open to eligible undergraduate students in the countries listed for the role.

• Pay: $100 per hour
• Work setup: Remote and asynchronous
• Education: Current junior or senior undergraduate at a research university
• Academic background: Strong academic standing and genuine subject-matter knowledge in your field
• Communication: Clear, well-reasoned English for explaining discipline-specific judgments
• Skills: Understanding of your field's visual conventions and technical vocabulary
• Equipment: Reliable internet access
• Helpful experience: Lab research, research assistance, independent study, or a thesis
• Helpful experience: Image-based or visual data such as microscopy, imaging, CAD, GIS, spectroscopy, diagrams, or archival materials
• Helpful experience: Annotation, data labeling, AI evaluation, large language models, multimodal systems, or quantitative methods

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind better artificial intelligence, including reviewing content, rating model responses, and labeling data. People with strong academic or professional knowledge help identify issues that general reviewers may miss, making their expertise useful for specialized evaluation projects.