Environmental Science Professional

AI Trainer Jobs; United States; Remote; USD 110,000 - 165,000; Full time

Job summary

AuraOne seeks an Environmental Science Professional to remotely evaluate AI outputs across environmental science reasoning, calculations, and research workflows. Reviewers grade derivations, reproduce results, and document the correct method to train the modeling team.

Bring graduate-level environmental science expertise, strong written reasoning, and the ability to work asynchronously for at least 10 hours per week. This is a remote contractor position focused on rigorous quality checks.

Qualifications

• Graduate-level training or equivalent in environmental science or related field.
• Hands-on experience publishing, teaching, or advising on environmental science topics.
• 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 environmental science methods and prior work.
• Reproduce or sanity-check key derivations, calculations, or claims.
• Flag dimensional, methodological, and citation errors with structured severity tags.
• Capture corrected reasoning or worked examples for model training.

Skills

Environmental science

Scientific reasoning

Quantitative analysis

Written reasoning

Education

PhD / Postdoc experience

Job description

Role details

Environmental Science Professional is a remote review track for evaluating AI outputs across environmental science 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: $100 / hr · Location: Remote — US-eligible · Contractor

Environmental Science Professional is a remote review track for evaluating AI outputs across environmental science reasoning, calculations, and research workflows.

About the role

Environmental Science Professional is a remote review track for evaluating AI outputs across environmental science 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.
Environmental science 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 environmental science methods, conventions, and prior work for Environmental Science Professional 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.Track STEM research review Work model Remote · Independent specialist contractor Compensation $100 / hr Eligible from US

What you should bring

• Graduate-level training or equivalent applied experience in environmental science or a closely related field for Environmental Science Professional 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.

Role signals

Example tasks

• Reproduce a environmental science 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

$100 / hr
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
• Environmental science
• AI model evaluation