Math AI Derivation Reviewer - Remote Contract

AuraOne; United States; On-site; USD 82,656 - 123,984; Part time

Job summary

AuraOne seeks a Mathematics Postdoc Researcher to remotely review AI outputs in mathematics reasoning, calculations, and research workflows. You will grade derivations, reproduce key steps, and document the correct method for training data.

As a contractor, you will work asynchronously with at least 10 hours per week, supporting the modeling team to flag errors and ensure methodological soundness in evaluations.

Qualifications

• Graduate-level training or equivalent applied experience in mathematics or related field.
• Experience publishing, teaching, or advising on the topic at a professional level.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning citing methods, papers, or worked examples.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current mathematics methods, conventions, and prior work for Mathematics Postdoc Researcher 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.

Skills

Scientific reasoning

Method validation

Citation review

Quantitative analysis

Mathematics

AI model evaluation

Education

PhD or equivalent experience

Graduate-level training or equivalent applied experience

Job description

AuraOne seeks a Mathematics Postdoc Researcher to remotely review AI outputs in mathematics reasoning, calculations, and research workflows. You will grade derivations, reproduce key steps, and document the correct method for training data.

As a contractor, you will work asynchronously with at least 10 hours per week, supporting the modeling team to flag errors and ensure methodological soundness in evaluations.