Remote Italian STEM Evaluation and Validation Specialist

AuraOne; United States; On-site; USD 52,348 - 59,236; Full time

Job summary

AuraOne is seeking a Bilingual Italian STEM Evaluation Specialist to remotely review AI outputs across Italian STEM reasoning, calculations, and research workflows. You will reproduce key results, document the correct method, and provide structured guidance for the modeling team to train on.

Ideal candidates have graduate-level training or equivalent experience in Italian STEM review, strong written reasoning citing methods or papers, and reliable async availability for at least 10 hours per

Qualifications

• Graduate-level training or equivalent applied experience in Italian STEM review or a closely related field.
• 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 Italian STEM review methods, conventions, and prior work for Bilingual Italian STEM Evaluation Specialist 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

Italian STEM review

Job description

AuraOne is seeking a Bilingual Italian STEM Evaluation Specialist to remotely review AI outputs across Italian STEM reasoning, calculations, and research workflows. You will reproduce key results, document the correct method, and provide structured guidance for the modeling team to train on.

Ideal candidates have graduate-level training or equivalent experience in Italian STEM review, strong written reasoning citing methods or papers, and reliable async availability for at least 10 hours per