Chemist with Python Proficiency - AI Trainer

We're building a talent pool of Chemistry professionals with Python proficiency to contribute to project-based AI development initiatives, focused on evaluating and enhancing frontier AI models.

Designed for chemistry specialists who enjoy deep technical problem-solving, this pipeline role is for those looking to apply their computational expertise to evaluate and push the boundaries of frontier AI models, relying on domain-specific tools such as GROMACS, PySCF, ORCA, Quantum ESPRESSO, or AutoDock Vina, with verifiable, code-graded answers run inside isolated Linux environments.

Key Responsibilities

• Identify an appropriate computational chemistry package and build problems whose solution genuinely hinges on that tool's core capabilities, whether force fields, integrators, electronic-structure methods, basis sets, or pseudopotential workflows
• Develop full Python solutions for each problem, providing all necessary input files, molecular geometries, and crystal structure definitions as required
• Establish the correct numerical output and define how close the AI model needs to get, using tolerance values appropriate to the chemical context
• Run the problem against the AI model across multiple parallel attempts, analyzing where it succeeds or falls short, and adjusting difficulty until the pass rate falls between 10% and 30%
• Tune molecular geometries, basis sets, and convergence thresholds iteratively, building an understanding of how the model navigates complex simulation environments
• Hand off completed tasks to a senior reviewer in your subfield and refine based on their feedback before final submission
  
  
  
  

Core Requirements

• Academic background in Chemistry or a closely related field
• At least 2 years of hands-on experience in chemistry research, applied work, or teaching
• Solid Python skills, applied to writing and validating computational solutions
• Capacity to build problems that cannot be solved without specialized computational chemistry software
• Excellent written and verbal communication skills in English
• Ability to work independently in a remote, fast-paced environment
  
  
  
  

Nice-to-Have

• Working knowledge of one or more domain-specific computational chemistry tools, including but not limited to GROMACS, LAMMPS, PySCF, ORCA, xtb, CREST, Quantum ESPRESSO, phonopy, pymatgen, AutoDock Vina, or GNINA, or a demonstrated ability to get up to speed independently
• Prior exposure to how frontier AI models approach complex simulation tasks
• Knowledge spanning more than one chemistry domain, such as molecular dynamics, quantum chemistry, or molecular docking
• Familiarity with containerized or sandboxed Linux execution environments
  
  
  
  

Please Note: Due to the high volume of applications, only shortlisted candidates will be contacted.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.