About this Role
We are seeking an experienced software engineer to contribute to the development of LLM evaluation and training datasets. The ideal candidate will have a strong background in software engineering and experience working with high-quality public GitHub repositories.
The primary responsibility of this role will be to analyze and triage GitHub issues across trending open-source libraries, set up and configure code repositories, evaluate unit test coverage and quality, modify and run codebases locally to assess LLM performance, and collaborate with researchers to design and identify repositories and issues that are challenging for LLMs.
Additionally, the successful candidate will have the opportunity to lead a team of junior engineers on projects and contribute to the growth of the organization's cutting-edge AI capabilities.
Key Responsibilities:
* Analyze and triage GitHub issues across trending open-source libraries
* Set up and configure code repositories, including Dockerization and environment setup
* Evaluate unit test coverage and quality
* Modify and run codebases locally to assess LLM performance
* Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs
Requirements:
* Strong experience with at least one programming language: Python, JavaScript, Java, Go, Rust, C/C++, C#, or Ruby
* Experience working with well-maintained, widely-used repositories with 500+ stars
* Proficiency with Git, Docker, and basic software pipeline setup
* Ability to understand and navigate complex codebases
* Comfortable running, modifying, and testing real-world projects locally
Benefits:
* Work in a fully remote environment
* Opportunity to work on cutting-edge AI projects with leading companies
Duration: This is a contractor assignment with a duration of 1 month, requiring a commitment of 20 hours per week with some overlap with PST time zone.