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Turing is hiring experienced software engineers to contribute to building LLM evaluation datasets for realistic software development tasks. You'll analyze GitHub issues, set up code repositories, and evaluate test coverage, shaping the future of AI-assisted software development in a fully remote work environment.
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 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
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 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:
Required Skills:
Experience working with well-maintained, widely-used repositories with 500+ stars
Note: Experience working with well-maintained, widely-used repositories (500+ stars) is required.
Nice to Have:
Referrals increase your chances of interviewing at Turing by 2x
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