AI Hardware Reasoning Reviewer — Remote Contractor (PhD/MS)

AuraOne, Inc.; United States; À distance; USD 69 000 - 124 000; Temps partiel

Résumé du poste

AuraOne, Inc. seeks a Hardware Expert (MSc or PhD) for AI Technical Reasoning Review. You will assess derivations, reproduce key results, and document correct methods so the modeling team can train on them.

The role requires strong hardware research background, ability to apply rubrics, and reliable async availability for at least 10 hours per week. Remote-US eligible; hourly compensation disclosed after interview.

Qualifications

• Graduate-level training or equivalent applied experience in hardware research review or a closely related field for Hardware Expert (MSc. or PhD) — AI Technical Reasoning Review work.
• Hands-on experience publishing, teaching, or advising on the topic at a professional level.
• Clear written reasoning that cites methods, papers, or worked examples.
• Reliable async availability for at least 10 hours per week.

Responsabilités

• Review AI outputs against current hardware research review methods, conventions, and prior work for Hardware Expert (MSc. or PhD) — AI Technical Reasoning Review 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.

Connaissances

Scientific reasoning

Method validation

Citation review

Quantitative analysis

Hardware research review

Formation

Graduate-level training / equivalent applied experience in hardware research review

Experience publishing, teaching, or advising at a professional level

Description du poste

AuraOne, Inc. seeks a Hardware Expert (MSc or PhD) for AI Technical Reasoning Review. You will assess derivations, reproduce key results, and document correct methods so the modeling team can train on them.

The role requires strong hardware research background, ability to apply rubrics, and reliable async availability for at least 10 hours per week. Remote-US eligible; hourly compensation disclosed after interview.