ML Research PhD Experts (ICML / NeurIPS / ICLR Publications)

AI Trainer Jobs; United States; Remote; USD 152,000 - 200,000; Full time

Benefits offered by this job

Remote work

Job summary

AI Trainer Jobs is seeking Remote ML Research PhD Experts to review AI outputs, reproduce key derivations, and document correct methods for model training. This independent contractor role requires rigorous scientific judgment and the ability to apply a standardized rubric across batches.

Responsibilities include grading, verifying claims, and providing clear, cited reasoning. Candidates should have a PhD or equivalent, publish or teach on ML topics, and be available for at least 10 hours per

Qualifications

• PhD or higher in ML or related field.
• Experience publishing or teaching on ML topics.
• Ability to apply multi-page rubrics consistently.
• Clear written reasoning citing methods or papers.
• Willingness to commit 10+ hours per week.

Responsibilities

• Review AI outputs against ml research review methods.
• Reproduce or sanity-check key derivations.
• Flag dimensional, methodological, and citation errors.
• Capture corrected reasoning to train the model.

Skills

Scientific reasoning

Method validation

Citation review

Quantitative analysis

ML Research review

Education

PhD or equivalent

Job description

ML Research PhD Experts (ICML / NeurIPS / ICLR Publications) is a remote review track for evaluating AI outputs across ml research phd experts 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: $110–$145 / hr · Location: Remote — US-eligible · Contractor

ML Research PhD Experts (ICML / NeurIPS / ICLR Publications) is a remote review track for evaluating AI outputs across ml research phd experts research review reasoning, calculations, and research workflows.

About the role

ML Research PhD Experts (ICML / NeurIPS / ICLR Publications) is a remote review track for evaluating AI outputs across ml research phd experts 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.
ML Research PhD Experts 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 ml research phd experts research review methods, conventions, and prior work for ML Research PhD Experts (ICML / NeurIPS / ICLR Publications) 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 $110–$145 / hr Eligible from US

What you should bring

• Graduate-level training or equivalent applied experience in ml research phd experts research review or a closely related field for ML Research PhD Experts (ICML / NeurIPS / ICLR Publications) 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 ml research phd experts 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

$110–$145 / 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
• ML Research PhD Experts 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

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.