Software Engineer Position Overview
We are seeking a skilled software engineer to contribute to our LLM evaluation and training datasets project.
The ideal candidate will have experience working with well-maintained, widely-used repositories on GitHub and be proficient in at least one programming language, including Python, JavaScript, Java, Go, Rust, C/C++, C#, or Ruby.
About the Project:
We are building verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop. The goal is to expand the dataset coverage to different types of tasks in terms of programming language, difficulty level, and more.
About the Role:
This position involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality. You should have strong analytical skills and be able to understand and navigate complex codebases.
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 in bug-fixing scenarios.
* Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs.
* Ongoing professional growth through feedback and self-assessment.
Requirements:
* Strong experience with at least one of the following languages: 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.
* Experience contributing to or evaluating open-source projects is a plus.
Benefits:
* Fully remote work environment.
* Opportunity to work on cutting-edge AI projects with leading LLM companies.
* Ongoing professional growth through feedback and self-assessment.
Commitment:20 hours per week with some overlap with PST. Employment type: Contractor assignment (no medical/paid leave). Duration of contract: 1 month with expected start date as next week.
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