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 world's fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You'll be at the forefront of evaluating how LLMs interact with real code, influencing the future ...