You will evaluate code patches generated by large language models for open source repositories. Your reviews will help assess whether each proposed change is correct, useful, and suitable for the repository.
You will also review work from other subject-matter experts and explain your decisions in clear written feedback. The goal is to produce consistent evaluations that help improve AI systems.
- Review AI-generated code patches for repositories you maintain.
- Assess proposed changes using software engineering judgment.
- Explain each assessment and technical decision in writing.
- Review submissions from other subject-matter experts.
- Evaluate changes in programming environments such as Python, C, C++, Java, TypeScript, Rust, and Go.
What it pays and takes
This is a part-time contractor role with flexible scheduling. Payment is based on completed tasks that meet project specifications.
- Pay: $150 to $300 USD per hour, output-based.
- Expected availability: 15 hours per week; listing details also specify 20+ hours per week.
- Work arrangement: globally remote, with eligibility limited to the listed countries.
- Open to candidates in: AE, AR, AT, BD, BE, BH, BR, CA, CH, CL, CO, DE, DK, DZ, EG, ES, ET, FR, GB, GH, GR, ID, IN, IT, JO, JP, KE, KG, KW, KZ, LB, LK, MA, MX, MY, NG, NL, OM, PE, PH, PK, PS, PT, QA, SA, SG, TH, TN, TW, US, UZ, VN, ZA.
- Language: professional fluency in English.
- Experience: active or demonstrable open source repository maintenance experience.
- Show a clear GitHub or GitLab profile with open source contributions.
- Experience reviewing contributor-submitted code and senior-level software engineering expertise are required.
- Experience with active contributor communities and pull request review is useful.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training is the human work behind systems that generate and evaluate content, including code. People with strong technical experience review examples, explain decisions, and provide feedback that helps AI systems produce more useful results.
