Senior Physics Adjudicator

AI Trainer Jobs; United States; Remote; USD 141,000 - 190,000; Full time

Job summary

AI Trainer Jobs is seeking a Senior Physics Adjudicator to remotely review and grade AI outputs in physics reasoning and research workflows. You will reproduce key results, assess assumptions, and document the correct method for model training.

Responsibilities include validating derivations, flagging errors with structured tags, and delivering worked examples for the team. This is a remote contractor role, paid hourly after interview, US-eligible.

Qualifications

• Graduate-level training or equivalent in physics or related field.
• Experience publishing, teaching, or advising at a professional level.
• Comfort using 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 physics methods, conventions, and prior work.
• Reproduce or sanity-check key derivations, calculations, or claims.
• Flag dimensional, methodological, and citation errors with severity tags.
• Capture corrected reasoning or worked examples for training data.
• Adjudicate disputed answers against textbooks, papers, or standards.

Skills

Graduate-level training

Multilingual fluency

Publish/teach/advise experience

Clear written reasoning

Async availability 10h/wk

Education

PhD, postdoc, or industry research experience

Job description

Senior Physics Adjudicator is a remote review track for evaluating AI outputs across physics 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.

Category: Scientific AI & Domain Experts Pay: $120 / hr Location: Remote — US-eligible Contractor

Senior Physics Adjudicator is a remote review track for evaluating AI outputs across physics reasoning, calculations, and research workflows.

Role details

About the role

Senior Physics Adjudicator is a remote review track for evaluating AI outputs across physics 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.
Physics 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 physics methods, conventions, and prior work for Senior Physics Adjudicator 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.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 physics or a closely related field for Senior Physics Adjudicator 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.

Example tasks

• Reproduce a physics 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
• Physics