About the Project
We are developing evaluation and training datasets for Large Language Models (LLMs) to improve their performance on realistic software engineering tasks.
Our approach involves building verifiable software development tasks based on public repository histories in a synthetic approach with human-in-the-loop, while expanding dataset coverage to different types of tasks, including programming language, difficulty level, and more.
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About the Role
We are seeking experienced software engineers (tech lead level) who are familiar with high-quality public GitHub repositories and can contribute to this project.
You should have experience working with well-maintained, widely-used repos with 500+ stars. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality.
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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.
* Opportunities to lead a team of junior engineers to collaborate on projects.
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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.
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Benefits
* Work in a fully remote environment.
* Opportunity to work on cutting-edge AI projects with leading LLM companies.