Domain Expert: Chemistry

Overview

Responsibilities

• Perform senior-level reviews of difficult or ambiguous chemistry questions and AI-generated answers.
• Judge scientific accuracy, logical consistency, mathematical correctness, clarity and instruction-following.
• Check reactions, mechanisms, structures, calculations, nomenclature, units, assumptions and conclusions.
• Find factual mistakes, unsupported statements, unsafe advice and invalid scientific reasoning.
• Guide structured resolution of disagreements among chemistry reviewers.
• Develop and improve grading rubrics, review instructions and quality standards.
• Advise client teams evaluating AI model performance and consult within relevant chemistry specialisms.
• Write rigorous explanations and feedback to publication-quality standards.
• Record review decisions and scientific consensus clearly and consistently.
• Follow project protocols, confidentiality obligations and quality standards.
• Take senior-review ownership of assigned batches and provide accurate, defensible and reliable evaluations.
• Clearly record errors, assumptions, calculations, mechanisms and review judgments; collaborate constructively with faculty-level reviewers and communicate professionally in client advisory sessions.
• Meet agreed deadlines and project quality requirements.

Requirements

• PhD in Chemistry, Chemical Sciences or a closely related discipline from an accredited institution.
• Faculty appointment at Assistant Professor level or above at an accredited US university or academic institution.
• At least three years of postdoctoral, faculty or equivalent professional research experience, and current involvement in chemistry research, teaching or academic supervision.
• Strong chemical principles, quantitative reasoning and laboratory practice.
• A demonstrated record of peer-reviewed chemistry or interdisciplinary scientific publications.
• Experience teaching undergraduate or graduate chemistry.
• Strong written communication and clear explanation of complex chemistry.
• Ability to assess different valid approaches and decide whether conclusions are scientifically defensible.
• Experience reviewing technical papers, research submissions, exam questions or scientific content.
• Ability to lead and document expert consensus, with close attention to detail and disciplined compliance with evaluation protocols.
• Disclose active equity, advisory, consulting, research-funding or paid relationships with AI companies; chemical, pharmaceutical, biotechnology or materials companies; scientific-software or lab-technology companies; research organisations whose work may appear; and any other commercial entities relevant to assigned cases. Disclosure does not automatically disqualify applicants but may affect work allocation.
• Applicants submit an updated CV with faculty appointment and research details, two recent peer-reviewed papers, and an approximately 300-word statement on experience in scientific writing, chemistry evaluation, peer review or AI research.
• Shortlisted candidates complete a qualification review, one interview and a brief paid calibration assignment before full engagement.
• An NDA is required before engagement; detailed work scope is provided after NDA execution.

Preferred

• Expertise in one or more of: organic; inorganic; physical; analytical; biochemistry/chemical biology; medicinal/pharmaceutical; computational/theoretical; materials/polymer; environmental; electrochemistry; surface/colloid; spectroscopy/chemical characterisation; thermodynamics/kinetics; catalysis/reaction mechanisms; synthetic; or industrial/process chemistry.
• Previous AI evaluation, scientific annotation or large-language-model research.
• Experience building scientific rubrics, benchmarks or assessment frameworks.
• Familiarity with scientific/computational chemistry tools such as Python, MATLAB, R, ChemDraw, Gaussian or ORCA.
• Molecular modelling, simulation, spectroscopy or scientific-data analysis experience.
• Journal peer-review or editorial experience; service on research, academic, grant-review, safety or ethics committees.
• Experience mentoring graduate students, postdocs or junior faculty.
• Active membership or participation in the American Chemical Society or another recognised chemistry organisation.
• Familiarity evaluating AI-generated structures, mechanisms, calculations and chemistry explanations.

Engagement and pay

• Independent contractor (1099), paid per task. No numerical pay rate is stated; compensation depends on experience, academic standing, research background and specialist area.
• Around 15 hours per week on average, rising to as much as 40 hours during peak batches.
• Four-week duration, with possible extension based on project requirements, needs and performance.
• Timeline depends on project and assignment availability. Work is flexible and intended to fit alongside academic responsibilities.
• The listing describes competitive compensation, remote flexibility, work on advanced AI projects, learning about AI training/evaluation, and collaboration with researchers from varied scientific backgrounds.

Eligibility

• United States only. Applicants must be US-based and hold an Assistant Professor or higher faculty appointment at an accredited US university or academic institution.
• Fully remote and mainly asynchronous, with occasional synchronous calls.