Chemistry AI Training Expert (Mexico)
anyone-ai
- Employment
- Contract
About the role
Location: Remote
Type: Contract / Part-time
Commitment: 20 hours per week
Compensation: Up to 40 USD / hr
Project duration: 2 months, with potential extension
Availability: Immediate start
About the role
We create high-quality STEM training data for frontier AI models that is directly used in training and evaluation workflows at leading AI labs.
We are looking for experts in Chemistry to design advanced, deterministic problems with exactly one verifiable correct answer. These problems should challenge modern AI systems with deep reasoning, domain knowledge, and computational rigor.
Projects may include computational chemistry, physical chemistry, analytical chemistry, chemical engineering-adjacent workflows, and chemistry tasks requiring specialized software tools.
What you’ll do
Design difficult chemistry problems that reflect real scientific workflows
Create deterministic tasks with one correct answer and full verified solutions
Develop reasoning-intensive and computationally grounded problems
Use Python and, where appropriate, domain-specific chemistry tools or simulation packages
Ensure all tasks are reproducible, technically precise, and clearly documented
Write concise and rigorous technical explanations in English
What we’re looking for
Bachelor's, Master’s or PhD in Chemistry or a related field
Research or industry experience involving computational or quantitative chemistry workflows
Strong Python skills; familiarity with scientific libraries
Strong understanding of modeling, numerical approaches, and chemical reasoning
Ability to design original, difficult problems that go beyond textbook recall
Excellent attention to detail and clear technical writing
Nice to have
Experience with computational chemistry, cheminformatics, spectroscopy analysis, molecular modeling, or specialized chemistry software
Experience with professional chemistry workflows involving simulation or data analysis tools
Experience creating technical evaluation content
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