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About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc. About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public Git Hub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality Why Join Us Turing is one of the worlds fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. Youll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research. What does day-to-day look like: Analyze and triage Git Hub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and workplace setup. Evaluating 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. Required Skills: Minimum 3+ years of overall experience Strong experience in Java Script / Type Script 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. Nice .
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