Domain Expert: Chemistry

About Turing: Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality data, evaluations, and reinforcement learning environments that improve model capabilities in coding, reasoning, tool use, and multimodality. In coding, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across Financial Services, Life Sciences, Healthcare, Retail, Automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Role Overview We are seeking Chemistry experts to contribute advanced scientific expertise to task design, data curation, and evaluation for frontier AI models and labs. This role focuses on developing rigorous chemistry tasks, reviewing complex scientific outputs, and advising client teams assessing AI-generated solutions. You will design tasks that evaluate whether AI agents can perform authentic chemistry work in a computational environment: inspecting scientific files, writing and running code, using chemistry software, debugging workflows, processing data, and producing verifiable scientific artifacts such as molecular models, simulation outputs, spectral analyses, and reproducible computational notebooks. The role is designed for experienced researchers, faculty, and industry specialists interested in improving the accuracy, reasoning, and reliability of AI systems in chemistry. What You’ll Do Day-to-Day Design scientifically rigorous chemistry tasks with clear objectives, appropriate inputs, and verifiable outcomes. Develop computational workflows that require AI agents to use chemistry software, write code, analyze data, and produce reproducible results. Lead expert review of complex or ambiguous chemistry problems and AI-generated responses. Review content within your areas of expertise, such as organic, inorganic, physical, analytical, computational, or theoretical chemistry. Assess molecular structures, reaction mechanisms, thermodynamic calculations, kinetic models, spectroscopic interpretations, and simulation results. Identify unsupported claims, incorrect chemical assumptions, methodological errors, and gaps in scientific reasoning. Verify chemical consistency, including stoichiometry, charge balance, stereochemistry, units, and the applicability of computational methods. Develop evaluation frameworks, scoring rubrics, reference solutions, and automated checks where appropriate. Facilitate structured resolution of scientific disagreements among reviewers. Provide expert guidance to client teams and clearly document evaluation decisions. Requirements PhD in Chemistry or a closely related discipline. Minimum three years of post-PhD research, teaching, or relevant industry experience. Current or recent experience in academic research, an industrial R&D environment, or a recognized research institution. Strong understanding of chemical principles, experimental design, and analytical methods relevant to your specialization. Specialized expertise in one or more chemistry domains. Experience with relevant computational tools, such as quantum chemistry packages, molecular simulation software, cheminformatics libraries, or spectroscopy analysis platforms. Proficiency in a programming or scripting language, such as Python, R, or an equivalent tool used in scientific workflows. Ability to design chemistry problems with clear assumptions, well-defined constraints, and independently verifiable solutions. Demonstrated research contributions through peer-reviewed publications, patents, or substantial scientific and computational projects. Ability to critically assess scientific literature, computational methods, experimental controls, and data interpretation. Strong written communication skills and the ability to explain chemical reasoning clearly. Ability to lead and document scientific consensus. Disciplined adherence to project protocols, confidentiality requirements, and quality standards. Preferred Qualifications Faculty appointment at the rank of Assistant Professor or above, or equivalent senior research or industry experience. Prior experience with AI evaluation, cheminformatics, machine learning for chemistry, or scientific dataset development. Experience with tools such as RDKit, Gaussian, ORCA, PySCF, GROMACS, or equivalent platforms relevant to your specialization. Experience developing reproducible computational notebooks, reference implementations, or automated validation workflows. Experience reviewing journal articles, research proposals, or technical reports. Experience teaching or mentoring graduate students, researchers, or scientific teams. Active involvement in professional societies such as ACS, RSC, or relevant specialist organizations. Familiarity with chemical safety, research ethics, data integrity, and reproducibility practices. Performance Expectations Take ownership of assigned task-design and review batches. Deliver chemically accurate tasks, reference solutions, and scientifically defensible evaluations. Ensure computational artifacts are reproducible and can be independently verified. Clearly document assumptions, methods, computational dependencies, uncertainty, and limitations. Distinguish experimentally established findings from computational predictions and speculative hypotheses. Maintain consistency and reliability when collaborating with other expert reviewers. Communicate constructively with client teams during advisory discussions. Meet agreed deadlines and follow established evaluation protocols. Disclose relevant equity, advisory, consulting, or employment relationships with organizations whose technologies or products may appear in project content. Disclosed conflicts do not automatically disqualify applicants but may influence assignment allocation. Perks of Freelancing with Turing Flexible, fully remote collaboration. Learn how advanced AI systems are trained and evaluated. Contribute to projects with leading AI and LLM companies. Apply your chemistry expertise to challenging, real-world AI evaluation problems. Collaborate with experts across disciplines and geographies. Potential for contract extension based on project needs and performance. Engagement Details Engagement type: Independent contractor. Anticipated commitment: An average of 15 hours per week, with up to 40 hours per week during peak periods. Duration: Four weeks. Timeline and assignments depend on project requirements. Fully remote and asynchronous, with occasional synchronous calls. NDA required upon engagement; detailed scope of work shared after NDA execution. Evaluation Process Submit your CV, including academic appointments or relevant research and industry experience. Include two recent peer-reviewed publications or equivalent scientific or computational contributions. Provide a brief statement of interest, approximately 300 words, describing your experience with chemistry problem design, computational workflows, structured technical writing, or AI evaluation. Applicants will be shortlisted based on qualifications and relevant domain expertise. Shortlisted applicants will participate in one interview. Successful applicants will complete a brief calibration assignment before full engagement.