Design graduate-level computational chemistry benchmarks for advanced AI systems using PySCF, Python, and electronic-structure expertise in a remote contract role paying $70–$100 per hour.
Coding & Software
100% Remote Hourly · $70–$100/hr
$70–$100/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Aug 11, 2026
Posted
Open worldwide
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About AI Training Work
AI training is the human side of building modern artificial intelligence. Specialists create benchmark tasks, evaluate model reasoning, and provide carefully designed examples that help advanced systems become more accurate and capable.
This is a fast-growing field with remote, flexible opportunities for people who bring valuable technical or subject-matter expertise. In this role, your computational chemistry knowledge will directly shape how AI systems approach scientific problems.
The Role
OpenTrain AI is seeking a Computational Chemistry AI Task Designer to create and refine graduate-level benchmark problems for advanced AI systems. You will combine research-level electronic-structure knowledge with rigorous problem and evaluation design.
The work will cover simulation, result interpretation, experiment planning, and discovery from partial information. You will design tasks that test multi-step calculations, exact answers, and strategic reasoning rather than raw computation alone.
Remote contract position
Part-time schedule with approximately 15–20 or more hours per week; the listing specifies 20+ hours weekly
Pay of $70–$100 per hour
English-language work
Listed as an entry-level opportunity, with graduate-level specialized training required
What You’ll Do
You will create original computational problems based on quantum chemistry research workflows and develop fully specified tasks that can be evaluated consistently. You will also design strategic problems in which an AI system must select queries or experiments, interpret partial results, and efficiently narrow possible explanations.
Your work will include building and testing scientific workflows, writing the task specifications, and refining challenges against AI models so they reach the intended level of difficulty.
Create benchmark problems involving quantum chemistry simulations and research workflows
Develop tasks testing multi-step calculations and exact-answer reasoning
Design strategic query-selection and experiment-planning problems using partial information
Create scenarios involving excited-state analysis, orbital diagnostics, method selection, and computational artifacts caused by method limitations
Write problem setups, oracle functions, and solution validators in Python
Evaluate problems against AI models and refine them to achieve the intended difficulty
Required Qualifications
This role requires graduate-level preparation in computational chemistry, electronic structure, or a related STEM field through an MS, PhD, or equivalent research experience. You should be comfortable translating research-level scientific judgment into precise computational tasks and validators.
Graduate-level computational chemistry or electronic-structure training, including an MS, PhD, or equivalent research experience
Hands-on experience with PySCF or another specialized scientific software library
Experience with Hartree–Fock, DFT, TDDFT, CASSCF, or post-HF calculations
Strong Python skills for scientific problem setups, oracle functions, and solution validators
Understanding of electronic-structure methods and their edge cases
Judgment in diagnosing excited-state, orbital, method-selection, and computational-artifact issues
Ability to design challenging problems that test strategic reasoning rather than raw computation
Ability to work independently, incorporate feedback, and use Linux or terminal-based remote compute environments
Helpful Background
The following experience is not required but can strengthen your fit for the role:
Experience with multiple scientific software tools
Benchmark or evaluation design
Scientific teaching, exam creation, or problem-set development
Computational reproducibility practices
Experience with containerized environments
Why Work With OpenTrain
OpenTrain brings together opportunities to teach and evaluate AI in one place while helping contributors build a durable portfolio around their specialized skills. Your work can demonstrate credible experience in scientific AI training and support a longer-term path in a rapidly growing technical field.
As a remote contributor, you can apply your computational chemistry expertise to cutting-edge AI development while working part time and managing your schedule around other commitments.
Work remotely with flexible part-time availability
Apply specialized scientific expertise to advanced AI systems
Build an AI-training portfolio around computational chemistry
Find opportunities through a free OpenTrain account
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