Computational Chemistry Researcher Task Author

You will turn real computational chemistry research into evaluation tasks for AI models. Each task should reflect work you have implemented, run, debugged, and validated yourself.

You will build connected scientific problems, explain how strong answers should be judged, and revise your work after structured review. You may also review and calibrate tasks submitted by other experts.

• Design original scientific-computing evaluation tasks based on your own research.
• Create a main problem with connected subproblems.
• Write a Python reference solution and tests that assess model outputs.
• Set clear standards for judging solutions without relying on hidden information or undisclosed passing thresholds.
• Revise tasks in response to structured review feedback.
• Optionally review and calibrate tasks from other experts in your field.

This is flexible, independent-contractor work with no fixed weekly schedule. You should be comfortable managing your time and working independently on task-based assignments.

• $100 per hour.
• Open to candidates in the countries listed for this role.
• Professional fluency in English.
• Research-track bachelor's study with research experience, or master's or PhD study, postdoctoral experience, or a recent degree in chemistry, chemical physics, chemical engineering, or a closely related field.
• Hands-on experience writing your own code, preferably Python, for chemical calculations or models.
• Ability to turn a real computational research workflow into a clearly specified task with a reference solution and tests.
• Experience in one or more areas such as quantum chemistry, molecular simulation, chemical kinetics, spectroscopy, electrochemistry, catalysis, chemometrics, biophysical chemistry, atmospheric chemistry, or thermodynamics.
• Work authorization without visa sponsorship is required. F-1 students, including OPT and CPT participants, are not eligible.

Public code, a thesis, or papers showing computational work you completed yourself can help demonstrate your experience. Experience with data annotation, data labeling, or AI and machine-learning evaluation is also useful.

Familiarity with research workflows using tools such as Gaussian or VASP, along with your own scripting, is helpful.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind systems that learn from examples, including writing, testing, and rating model outputs. Researchers with specialized knowledge help make these evaluations accurate when the work involves advanced scientific topics.