Open role at a frontier AI lab
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In this role, you’ll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.
Key Responsibilities:
• Design, evaluate, and critique chemistry and computational chemistry problems, workflows, and reasoning chains to support AI benchmarking initiatives.
• Provide expert-level insights on reaction mechanisms, synthesis planning, spectroscopy analysis, molecular simulations, and electronic structure methods.
• Assess and optimize experimental protocols, simulation parameters, and software configurations for accuracy and reproducibility.
• Analyze chemical, spectroscopic, and simulation data and provide actionable recommendations.
• Leverage domain knowledge to guide the development and validation of chemistry-related AI models and tools.
• Communicate complex scientific concepts clearly, both in writing and verbally, to technical and non-technical collaborators.
• Document findings, methodologies, and best practices to ensure knowledge transfer across the customer’s team.
Areas of Expertise (we welcome applicants from any of the following):
• Organic synthesis & reaction mechanisms
• Inorganic & organometallic chemistry
• Physical & theoretical chemistry
• Analytical chemistry & spectroscopy
• Computational chemistry & molecular dynamics
• Cheminformatics & drug discovery
• Materials science & polymer chemistry
Required Skills and Qualifications:
• PhD in chemistry, computational chemistry, chemical biology, materials science, or a closely related field.
• Hands-on research lab experience, including wet lab experience for experimental subfields, or extensive simulation-heavy research for computational subfields.
• Deep expertise in at least one of the areas listed above.
• Professional written and spoken English (C1 or higher).
• Proficiency in Python and/or industry-standard tools in your subfield (e.g., Gaussian, ORCA, Psi4, GROMACS, LAMMPS, RDKit).
• Excellent quantitative, analytical, and scientific reasoning skills.
• Outstanding written and verbal communication abilities, with the ability to clearly document and explain technical concepts.
• Track record of rigorous scientific problem-solving in complex chemistry domains.
• Academic experience (postdoc, research scientist, faculty, or equivalent), strongly preferred.
• Peer-reviewed publications, patents, or contributions to open-source scientific software.
• Experience with AI/ML-assisted chemistry workflows or benchmarking.
• Background in drug discovery, reaction prediction, or retrosynthesis.