Students Across All Disciplines (Undergrad, Grad)

Job Description

This is a remote, project-based role for currently enrolled graduate students and strong senior undergraduates across academic disciplines to contribute to an AI evaluation research project. You will apply your domain expertise to assess, write, and validate content that requires genuine subject-matter knowledge — the kind that only comes from years of coursework, lab work, or field research in your area.

Work is asynchronous, assigned on a project-by-project basis, and structured to respect your existing academic schedule. You choose which projects to accept. Expect an estimated commitment of up to 10 hours per week for each project window you take on. This role offers strong pay, genuine intellectual engagement, and a meaningful addition to your research and professional portfolio.

Why Apply

• Strong compensation Earn $800–$1,500 per project week depending on discipline and seniority, with top candidates eligible for premium rates.
• Intellectually engaging work Your domain knowledge directly shapes how AI systems understand your field — not busywork, but substantive expert evaluation.
• Fully flexible schedule Asynchronous work you fit around your academic commitments. Accept only the projects that work for your schedule.

Responsibilities

• Apply your domain expertise to evaluate, write, and validate content that requires genuine academic knowledge in your field
• Assess materials for accuracy, depth, and quality from the perspective of a trained specialist in your discipline
• Identify errors, ambiguities, or gaps that would be invisible to a non-expert reviewer
• Provide structured written rationale and feedback for each evaluation decision
• Interpret and respond to visual or diagrammatic content specific to your field (e.g. schematics, spectra, maps, clinical images, artworks, data charts)
• Complete a defined set of annotation tasks within each project window (10–20 hrs/week)

Required Qualifications

• Currently enrolled in a PhD, Master's, MD, or MD/PhD program — OR a senior undergraduate at a research university with strong academic standing in your field
• Ability to produce clear, well-reasoned written explanations of domain-specific judgments
• Deep familiarity with the visual conventions and technical vocabulary of your discipline (e.g. reading spectra, interpreting schematics, analyzing maps, evaluating clinical images, or formal visual analysis)
• Reliable internet access and availability for asynchronous, remote work
• Strong English writing proficiency

Preferred Qualifications

• PhD Year 2+ or MD/PhD student with completed qualifying exams or clinical rotations (MS3/MS4)
• Active research experience involving image-based or visual data in your field (microscopy, imaging, diagrammatic modeling, CAD, GIS, spectroscopy, archival visual materials, etc.)
• Prior annotation, data labeling, or AI evaluation experience
• Affiliation with a top research university or program with strong standing in your discipline
• Familiarity with AI tools, large language models, or multimodal systems, even at a general level
• Quantitative methods training (relevant across science, social science, business, and engineering tracks)

Company Description

AfterQuery is a research lab investigating the boundaries of artificial intelligence through novel datasets and experimentation.

We're backed by top investors, including Y Combinator and Box Group, and support all leading AI labs.