Remote Applied Scientist | AI Research Review & Validation

AuraOne, Inc.; United States; On-site; USD 55,000 - 83,000; Full time

Job summary

AuraOne, Inc. is seeking an Applied Scientist reviewer to evaluate AI outputs across research science reasoning, calculations, and workflows. You will reproduce key derivations, flag errors, and document correct methods to train the modeling team.

Ideal candidates have graduate-level research experience, a track record of publishing or teaching, and the ability to apply rubrics consistently across large batches with reliable async availability for at least 10 hours per week.

Qualifications

• Graduate-level training or equivalent applied experience in research science or a closely related field.
• Experience publishing, teaching, or advising 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 research science methods, conventions, and prior work for Applied Scientist 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

Graduate-level training

Professional publishing

Rubrics comprehension

Clear written reasoning

Async availability

Education

Graduate degree in research science

Job description

AuraOne, Inc. is seeking an Applied Scientist reviewer to evaluate AI outputs across research science reasoning, calculations, and workflows. You will reproduce key derivations, flag errors, and document correct methods to train the modeling team.

Ideal candidates have graduate-level research experience, a track record of publishing or teaching, and the ability to apply rubrics consistently across large batches with reliable async availability for at least 10 hours per week.