Computational Chemistry Problem Designer (PhD Required)

About OpenTrain

OpenTrain is the #1 platform for building careers in AI training and data labeling. We connect subject-matter experts with projects that shape state-of-the-art AI systems — from designing datasets and problems to reviewing model outputs — and support contributors at every stage of their careers.

About AI training and this work

AI training is the human side of model development: experts create and validate examples that teach models to reason, compute, and behave appropriately. These projects are often remote, flexible, and accessible to people with domain expertise — and contributors directly influence how cutting-edge AI systems perform.

This role sits at the intersection of domain science and software: you will create content that trains and evaluates models while using code and scientific workflows to verify correctness.

• 100% remote, project-based, and often flexible with hours.
• Work influences model behavior and helps translate research workflows into reproducible training artifacts.

The role

You will design original computational chemistry problems that require advanced reasoning in physical chemistry, quantum chemistry, and molecular modeling. Deliverables include rigorous, research-grade problem statements and comprehensive, fully verified solutions.

Validation must be performed using Python and appropriate computational chemistry libraries so that problems reflect authentic research workflows and are not easily solvable by hand. Work is part-time, contractor-based, and paid per hour with compensation tied to complexity and expertise required.

• Create problems that model realistic research scenarios and workflows.
• Provide fully worked, verified solutions implemented and validated in code.

What you'll do

• Design original, research-level problem statements in computational and quantum chemistry.
• Develop complete, reproducible solution sets and explain methodology and approximations.
• Implement and validate solutions in Python using computational chemistry libraries (your choice of suitable libraries).
• Ensure problems are not solvable purely by hand and require computational workflows.
• Annotate and review code used for verification, and produce clear, publication-quality writeups.

Requirements

Candidates must meet all of the following. We cannot consider applicants who do not provide a CV in English that states their English proficiency level and includes an email address and phone number.

• PhD in chemistry or a closely related field.
• 3+ years of computational chemistry experience and research-level familiarity with quantum and physical chemistry.
• Proficient in Python and experienced with computational chemistry libraries.
• Strong scientific writing skills and experience developing research problems.
• Hands-on experience annotating, reviewing, or otherwise working with code for verification and validation.

Location & eligibility notes

OpenTrain acquires contributors worldwide, but there are location restrictions. Please note we cannot acquire contributors from the following locations:

Iran; Cuba; North Korea; Syria; Sudan; Venezuela; Myanmar; Russia; Belarus; Palestine; Switzerland; China; Taiwan; Kenya; the listed U.S. states and various territories and remote islands. If you are unsure whether your location is eligible, include your country and residence details when you apply and we will confirm eligibility.

Compensation & time commitment

This is a part-time contractor role requiring 20+ hours per week. Compensation is paid per hour and linked to task complexity and required expertise.

• Pay: hourly, $15–$60 per hour (final rate depends on task complexity and required expertise).
• Employment type: Contractor, Part-time. Time requirement: 20+ hours/week.

How to apply

Apply through OpenTrain with a CV in English that states your English proficiency and includes a working email address and phone number. Your CV should highlight your PhD, computational chemistry projects, relevant Python code or repositories, and examples of problem development or research problems you have authored.

We review applications for domain expertise, coding proficiency, and demonstrated experience creating research-level problems. Successful applicants will be invited to a short technical/sample task to verify fit.