Chemistry Domain Expert - Senior Reviewer at Turing

Chemistry Domain Expert (Senior Reviewer) | Contractor | Remote (US)

Turing is hiring US-based academic chemists for its Senior Reviewer track to curate and evaluate high-quality chemistry data for frontier AI models and research laboratories. You will review complex chemistry problems and AI-generated solutions, resolve disagreements among reviewers, develop evaluation frameworks, and advise client teams assessing AI model outputs.

What You'll Do

• Conduct senior-level reviews of complex or ambiguous chemistry problems and AI-generated solutions.
• Evaluate responses for scientific accuracy, logical consistency, mathematical correctness, and clarity.
• Verify chemical reactions, mechanisms, structures, calculations, nomenclature, units, and conclusions.
• Identify factual errors, unsupported claims, unsafe recommendations, and invalid scientific reasoning.
• Facilitate structured resolution of disagreements among chemistry reviewers.
• Develop and refine evaluation rubrics, review guidelines, and quality standards.
• Provide expert advisory support to client teams reviewing AI model performance.
• Write technically rigorous, publication-quality explanations and reviewer feedback.

Requirements

• PhD in Chemistry or a closely related discipline from an accredited institution.
• Faculty appointment at the rank of Assistant Professor or above at an accredited US university.
• At least three years of postdoctoral, faculty, or equivalent professional research experience.
• Active involvement in chemistry research, teaching, or academic supervision.
• Demonstrated publication record in peer-reviewed chemistry or interdisciplinary journals.
• Experience teaching undergraduate or graduate-level chemistry courses.
• Experience reviewing technical papers, research submissions, or scientific content.
• Strong written communication skills and attention to detail.

Expertise in one or more areas is preferred: organic, inorganic, physical, analytical, biochemistry, medicinal, computational, materials, environmental, electrochemistry, spectroscopy, thermodynamics and kinetics, catalysis, synthetic, or industrial chemistry.

Preferred: prior experience with AI evaluation, scientific data annotation, or LLM research; familiarity with tools such as Python, MATLAB, R, ChemDraw, Gaussian, or ORCA; journal peer-review or editorial experience; committee service; mentoring experience.

Pay and Schedule

• Engagement type: Independent contractor (1099), pay per task.
• Compensation determined based on experience, academic standing, research background, and area of expertise.
• Approximately 15 hours per week on average, with up to 40 hours per week during peak batches.
• Duration: Four weeks, with potential extension depending on project requirements.
• Flexible, primarily asynchronous work designed to complement academic responsibilities, with occasional synchronous calls.

Location

Fully remote within the United States.

How to Apply

Applicants must submit an updated CV with faculty appointment and research details, two recent peer-reviewed publications, and a brief statement of interest (~300 words). Shortlisted applicants complete a qualification review, one interview round, and a brief paid calibration assignment before full engagement. Applicants must disclose any active equity, advisory, consulting, research-funding, or paid relationships with AI companies, chemical/pharmaceutical/biotech/materials companies, or other relevant commercial entities. An NDA is required before engagement.