You will help build and assess software engineering tasks used in AI training. The work focuses on public GitHub repositories, real bug-fixing scenarios, and how well large language models handle software development problems.
You will also work with researchers and lead junior engineers on collaborative projects.
- Analyze and triage issues in trending open-source libraries.
- Set up and configure repositories, including Docker environments and basic software pipelines.
- Review unit test coverage and assess test quality.
- Run and modify codebases locally to evaluate LLM performance on bug-fixing tasks.
- Work with researchers to find repositories and issues that are challenging for LLMs.
- Lead junior engineers on collaborative projects.
What it pays and takes
This is a remote, part-time contractor assignment. Pay details are not provided in the listing.
- Hours: Choose 20, 30, or 40 hours per week, with at least 20 hours required.
- Schedule: Commit to four hours of overlap with Pacific Standard Time.
- Location: Applicants must be based in India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, or Mexico.
- Language: English.
- Experience: At least three years of overall software engineering experience.
- Technical skills: Strong Ruby experience, plus Git, Docker, and basic software pipeline setup.
- You must be able to understand complex codebases and run, modify, and test real-world projects locally.
- Helpful background includes open-source contributions or evaluation, LLM research or evaluation, and developer tools or automation agents.
How it works
Apply on OpenTrain with your resume and then complete the application on the hiring site.
About AI training work
AI training work uses human-reviewed examples, tests, and feedback to improve how AI systems respond. Software engineers are needed to create realistic coding tasks and judge whether model-generated code works correctly.
