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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 involves building verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop, while expanding dataset coverage to different programming languages and difficulty levels.
We are looking for experienced software engineers (tech lead level) familiar with high‑quality public GitHub repositories to contribute to this project. This role involves hands‑on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality.
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.
At least 4 hours per day and a minimum of 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week)
Contractor assignment (no medical/paid leave)
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