Member of Technical Staff, Research Engineering

AI Trainer Jobs; United States; Remote; USD 330,624,000 - 358,176,000; Full time

Job summary

AI Trainer Jobs seeks a Member of Technical Staff, Research Engineering for a remote contractor track to evaluate AI outputs across research workflows. You will review derivations, reproduce key steps, and flag errors with structured notes.

This role emphasizes scientific reasoning, citation quality, and clear written explanations. A PhD, postdoc, or equivalent research experience plus hands-on publication or teaching is required.

Qualifications

• PhD, postdoc, or industry research experience in the topic area.
• 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 research review 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

Scientific reasoning

Method validation

Citation review

Quantitative analysis

Multilingual fluency

Education

PhD or equivalent research experience

Job description

Member of Technical Staff, Research Engineering is a remote review track for evaluating AI outputs across member of technical staff research engineering research review reasoning, calculations, and research workflows.

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

Member of Technical Staff, Research Engineering is a remote review track for evaluating AI outputs across member of technical staff research engineering research review reasoning, calculations, and research workflows.

About the role

Member of Technical Staff, Research Engineering is a remote review track for evaluating AI outputs across member of technical staff research engineering research review reasoning, calculations, and research workflows.
Member of Technical Staff Research Engineering 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 member of technical staff research engineering research review methods, conventions, and prior work for Member of Technical Staff, Research Engineering 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 member of technical staff research engineering research review or a closely related field for Member of Technical Staff, Research Engineering 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 member of technical staff research engineering 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
• Member of Technical Staff Research Engineering research review

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

• - 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.