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Turing seeks experienced software engineers to contribute to LLM evaluation and training datasets. This role involves hands-on work with high-quality GitHub repositories, focusing on automation and software quality evaluation while working in a remote environment on cutting-edge AI projects.
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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:
Note: Experience working with well-maintained, widely-used repositories (500+ stars) is required.
Nice to Have:
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