The work
You will help evaluate how advanced AI models reason through difficult scientific and technical problems. The work centers on research and evaluation, not production engineering.
You will use your expertise to define what strong answers should include, assess model outputs, and explain your decisions in clear technical writing.
- Design realistic technical scenarios and problem sets in your area of expertise.
- Write expert-level reference solutions and grading rubrics.
- Evaluate AI-generated answers for correctness, depth, and sound domain judgment.
- Write structured technical explanations and feedback that make expert decisions understandable.
What it pays and takes
The provided listing does not include pay details. The role is described as a remote, part-time contract position with a commitment of at least 20 hours per week.
- Hours: 20 or more hours per week.
- Work arrangement: Remote, independent, and asynchronous.
- Location: Open to candidates in the countries listed for this role, including the United States, Canada, the United Kingdom, Australia, and others.
- Language: Professional fluency in English.
- Education: A PhD or doctorate in a relevant scientific or computational field.
- Experience: At least 10 years of experience and current or recent hands-on activity in the field.
- Expertise: Formal methods, computational science, mathematics, physics, chemistry, or biology.
- Communication: Strong written communication for technical explanations and structured feedback.
- Helpful background: Research publications, open-source contributions, recognized domain work, peer review, code review, grading, or editing.
- Specialist experience may include Lean or Coq theorem proving, computational biology or genomics, and condensed-matter or quantum physics.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training work is the human side of building artificial intelligence. Specialists create examples, write answers, and review model outputs so AI systems can produce more accurate and useful results. People with deep subject expertise are needed for difficult technical evaluations because they can judge reasoning that general reviewers cannot.
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