Deep Research Research QA Specialist

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

Job summary

AI Trainer Jobs is seeking a Deep Research Research QA Specialist for a remote review track to evaluate AI outputs across deep research and QA workflows. Reviewers grade derivations, reproduce results, and document methods so the modeling team can train on it.

This contractor role offers an hourly rate of $120 and US eligibility for remote work. You will work independently on tasks such as reproducing derivations, flagging errors, and providing clear, citable reasoning across long batches.

Qualifications

• Graduate-level training or equivalent applied experience in deep research QA review or related field.
• Hands-on experience publishing, teaching, or advising on the topic at a professional level.
• Clear written reasoning that cites methods, papers, or worked examples.

Responsibilities

• Review AI outputs against current deep research QA review methods and prior work.
• Reproduce or sanity-check key derivations, calculations, or experimental claims.
• Flag dimensional, methodological, and citation errors with structured severity tags.
• Capture corrected reasoning or worked examples for training purposes.

Skills

Graduate-level training

Hands-on publishing/teaching

Clear written reasoning

Reliable async availability

Multilingual fluency

Education

PhD/Postdoc or equivalent

Tools

Web research

Browser automation

Job description

Deep Research Research QA Specialist is a remote review track for evaluating AI outputs across deep research research qa research review 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

Deep Research Research QA Specialist is a remote review track for evaluating AI outputs across deep research research qa research review reasoning, calculations, and research workflows.

About the role

Deep Research Research QA Specialist is a remote review track for evaluating AI outputs across deep research research qa research review 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.
Deep Research Research QA research review 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 deep research research qa research review methods, conventions, and prior work for Deep Research Research QA 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.

Role details

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 deep research research qa research review or a closely related field for Deep Research Research QA Specialist 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 deep research research qa research review 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
• Deep Research Research QA research review
• Web researchSource grounding
• Browser automation
• Deep
• Research

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.
- 01 Confirm profile and eligibility details.
- 02 Attach this role deliberately.
- 03 Receive a human review decision or follow-up.
Placement timing depends on program demand and reviewer confirmation.