STEM Professor — AI Academic Review and Evaluation.

STEM Professor — AI Academic Review and Evaluation is a remote review track for evaluating AI outputs across stem research reasoning, calculations, and research workflows. Reviewers grade derivations and assumptions, reproduce key results, and document the correct method so the modeling team can train on it.

STEM research models live or die on whether their derivations actually hold up under scrutiny. AuraOne uses scientific specialists to grade outputs the way a peer reviewer would — checking assumptions, reproducing key steps, and capturing the right method alongside the wrong one.

Scientific, analytical, and research-heavy roles for domain experts across STEM and technical knowledge work.

• ↳Review AI outputs against current stem research methods, conventions, and prior work for STEM Professor — AI Academic Review and Evaluation assignments.
• ↳Reproduce or sanity-check key derivations, calculations, or experimental claims.
• ↳Flag dimensional, methodological, and citation errors with structured severity tags.
• ↳Capture the corrected reasoning or worked example so the modeling team can train on it.
• ↳Adjudicate disputed answers against textbooks, papers, or community standards.
• ↳Maintain reviewer-quality scores in inter-rater calibration cycles.

• ↳Graduate-level training or equivalent applied experience in stem research or a closely related field for STEM Professor — AI Academic Review and Evaluation work.
• ↳Hands-on experience publishing, teaching, or advising on the topic at a professional level.
• ↳Comfort applying multi-page rubrics consistently across long batches.
• ↳Clear written reasoning that cites methods, papers, or worked examples.
• ↳Reliable async availability for at least 10 hours per week.

$150 / hr

Expected schedule: contractor, remote specialist work with program-defined task volume and review pacing.

• Scientific reasoning
• Method validation
• Citation review
• Quantitative analysis
• STEM research
• AI model evaluation

AuraOne uses a shared specialist intake to confirm track fit, review readiness, and the best queue for your profile. Applications submitted from partner job boards carry the source, role, and category on the apply URL.