Graduate Math Model Evaluator

AI Trainer Jobs; United States; Remote; USD 69,000 - 76,000; Part time

Job summary

AI Trainer Jobs is seeking a Graduate Math Model Evaluator to remotely review AI outputs across graduate math model research, reasoning, calculations, and workflows.

Evaluators judge derivations, reproduce key steps, and document the correct method so the modeling team can train on it. The role emphasizes scoring accuracy, method validation, and citation review.

Qualifications

• Graduate-level training or equivalent applied experience in graduate math model research review.
• 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.

Responsibilities

• Review AI outputs against current graduate math model research review methods, conventions, and prior work for Graduate Math Model Evaluator 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.

Skills

Scientific reasoning

Method validation

Citation review

Quantitative analysis

Graduate Math Model review

Formal reasoning

Proof review

Education

PhD

Postdoc

Job description

Graduate Math Model Evaluator is a remote review track for evaluating AI outputs across graduate math model research review 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.

Category: Math, Reasoning & Formal Methods · Pay: $50 / hr · Location: Remote — US-eligible · Contractor

Graduate Math Model Evaluator is a remote review track for evaluating AI outputs across graduate math model research review reasoning, calculations, and research workflows.

About the role

Graduate Math Model Evaluator is a remote review track for evaluating AI outputs across graduate math model research review reasoning, calculations, and research workflows.

Graduate Math Model research review 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.

Judge mathematical reasoning and theorem proving. Long proof chains included.

Responsibilities

• Review AI outputs against current graduate math model research review methods, conventions, and prior work for Graduate Math Model Evaluator 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.

Role details

Track STEM research review Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Graduate-level training or equivalent applied experience in graduate math model research review or a closely related field for Graduate Math Model Evaluator 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.

Example tasks

• Reproduce a graduate math model research review derivation from a model output and flag any algebraic or dimensional errors.
• Grade a model's literature summary against the cited papers and rate the citation quality.
• Adjudicate a disputed answer between two reviewers using textbook methods.
• Audit a 25-row batch for rubric consistency and report drift to the program lead.

Useful experience

• PhD, postdoc, or industry research experience in the topic area.
• Prior work reviewing AI-assisted research tooling and its failure modes.
• Multilingual fluency for non-English papers and corpora.

Compensation and schedule

Hourly rate confirmed after the interview process.

Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Scientific reasoning
• Method validation
• Citation review
• Quantitative analysis
• Graduate Math Model research review
• Formal reasoning
• Proof review
• Graduate
• Math

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.

• - 01 Confirm profile and eligibility details.
• - 02 Attach this role deliberately.
• - 03 Receive a human review decision or follow-up.

Placement timing depends on program demand and reviewer confirmation.