Remote User Research & Feedback Synthesis Evaluator

Auraone; United States; Remoto; USD 110.000 - 165.000; Tempo pieno

Vantaggi offerti da questo lavoro

Remote work

Descrizione del lavoro

AI Trainer Jobs in the United States is seeking remote Evaluators to review AI outputs against user research methods, reproduce key steps, and document the correct method so the modeling team can train on it. Reviewers grade derivations, check assumptions, reproduce results, and capture the right method alongside the wrong one.

We value scientific and technical domain expertise, multilingual ability, and reliable async availability for at least 10 hours per week.

Competenze

• Graduate-level training or equivalent applied experience in user/customer research and feedback synthesis research 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.

Mansioni

• Review AI outputs against current user/customer research and feedback synthesis research review methods, conventions, and prior work for Evaluator 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.

Conoscenze

Scientific reasoning

Method validation

Citation review

Quantitative analysis

User/customer research

Formazione

PhD/doctorate or industry research experience

Strumenti

Rubrics

Documentation

Descrizione del lavoro

AI Trainer Jobs in the United States is seeking remote Evaluators to review AI outputs against user research methods, reproduce key steps, and document the correct method so the modeling team can train on it. Reviewers grade derivations, check assumptions, reproduce results, and capture the right method alongside the wrong one.

We value scientific and technical domain expertise, multilingual ability, and reliable async availability for at least 10 hours per week.