Computational Mathematics Expert

AuraOne; United States; On-site; USD 83,000 - 165,000; Full time

Job summary

AI Trainer Jobs seeks a Computational Mathematics Expert to remotely review AI outputs across mathematics reasoning, calculations, and research workflows. You will reproduce key results, check derivations, and document methods so the modeling team can train on correct and incorrect approaches.

Responsibilities include grading against established methods, flagging errors with structured notes, and capturing worked examples for ongoing model improvement. This is an independent contractor role.

Qualifications

• Graduate-level training or equivalent applied experience in mathematics or a closely related field for Computational Mathematics Expert 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.

Responsibilities

• Review AI outputs against current mathematics methods, conventions, and prior work for Computational Mathematics Expert 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

Mathematics

Education

PhD, postdoc or industry research experience in mathematics

Job description

About the role

Computational Mathematics Expert is a remote review track for evaluating AI outputs across mathematics 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.
Mathematics 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.
Bring scientific and technical domain expertise into AI reasoning, research, and dataset review.

Responsibilities

• Review AI outputs against current mathematics methods, conventions, and prior work for Computational Mathematics Expert 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 mathematics or a closely related field for Computational Mathematics Expert 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.

Role signals

Example tasks

• Reproduce a mathematics 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
• Mathematics