Computational Chemistry AI Task Designer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help specialized contributors discover projects, create a professional AI training profile, and apply to opportunities that match their expertise. Creating an OpenTrain account is free.

• Remote contract work with flexible scheduling
• Build experience in a fast-growing AI training industry
• Use your scientific expertise to influence how advanced AI systems are evaluated

About AI Training and Scientific Evaluation

AI training is the human side of building artificial intelligence. Researchers and specialists create examples, tests, and evaluations that help modern models learn to reason, follow instructions, and produce reliable results. In scientific AI evaluation, subject-matter experts design demanding problems that reveal whether a model can apply judgment rather than simply repeat familiar calculations.

• Work on cutting-edge evaluations for advanced AI systems
• Translate real scientific workflows into measurable challenges
• Help test model reasoning with incomplete information and complex decisions

The Computational Chemistry AI Task Designer Role

OpenTrain is recruiting a Computational Chemistry AI Task Designer to create demanding benchmark problems based on real computational chemistry and electronic-structure workflows. You will design challenges involving simulations, result interpretation, experiment planning, and discovery from incomplete information.

The work focuses on scientific judgment and strategic reasoning, not only whether an AI system can execute a sequence of calculations. You will work independently in Linux or terminal-based remote compute environments and refine task difficulty by testing problems against advanced AI models.

• Remote contractor position
• Advertised compensation of $70-$100 USD per hour
• Availability requested at 15-20 hours per week or more
• Default commitment of 40 hours per week
• English-language work
• Open worldwide

What You'll Do

You will turn your computational chemistry expertise into original, fully specified AI evaluation tasks. Each challenge should reflect meaningful scientific practice while making the expected reasoning, computation, and validation clear.

• Create original, graduate-level computational chemistry problems grounded in real scientific workflows
• Design multi-step calculation tasks that test complex execution
• Develop challenges requiring AI systems to plan queries or experiments, interpret partial results, and narrow possible explanations
• Use PySCF for Hartree-Fock, DFT, TDDFT, CASSCF, and post-Hartree-Fock quantum chemistry problems
• Build tasks involving excited-state analysis, orbital diagnostics, method selection, and computational artifacts caused by methodological limitations
• Write problem setups, oracle functions, and solution validators in Python
• Test each problem against advanced AI models and refine its difficulty based on observed performance

Required Qualifications

This role requires graduate-level scientific training and substantial hands-on experience with computational chemistry or electronic-structure workflows. Your background should demonstrate that you can distinguish meaningful scientific reasoning from raw computation and identify where software or methodology may produce misleading results.

• Graduate-level training in a relevant STEM field, such as an MS, PhD, or equivalent research experience
• Deep hands-on experience with computational chemistry or electronic-structure workflows
• Proven proficiency with PySCF or a comparable scientific software library
• Experience across quantum chemistry workflows, including method selection and excited-state or orbital analysis
• Strong Python programming ability for scientific problem construction and validation
• Ability to reason about software limitations, computational artifacts, edge cases, and challenge validity
• Comfort working independently in Linux or terminal environments with remote compute sandboxes

Helpful Background

The following experience would be useful when designing realistic, reproducible, and difficult scientific AI evaluations. These areas are helpful additions to the required computational chemistry and programming background.

• Research publications, open-source contributions, or professional work demonstrating scientific software expertise
• Experience with multiple scientific software tools
• Benchmark or evaluation design
• Scientific teaching, exam creation, or problem-set development
• Computational reproducibility
• Containerized environments

How to Get Started

Create a free OpenTrain account and build a profile that highlights your computational chemistry, electronic-structure, PySCF, and Python experience. You can apply in minutes and use OpenTrain to grow a longer-term career in AI training and specialized data work.

• Prepare details of your graduate training and research experience
• Highlight relevant PySCF or comparable scientific software work
• Showcase Python, Linux, validation, and benchmark-design experience
• Apply through OpenTrain for consideration as a remote contractor