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We are building LLM evaluation and training datasets to train LLMs to solve realistic software engineering problems. The approach involves creating verifiable SWE tasks based on public repository histories in a synthetic manner with human‑in‑the‑loop, and expanding dataset coverage across languages and difficulty levels.
We seek an experienced software engineer (tech lead level) familiar with high‑quality public GitHub repositories to contribute to this project. Responsibilities include hands‑on software engineering, development environment automation, issue triaging, and evaluation of test coverage and quality.
Turing is one of the world’s fastest‑growing AI companies. This role places you at the forefront of evaluating how LLMs interact with real code, blending 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. Options: 20 hrs/week, 30 hrs/week, or 40 hrs/week.
Contractor assignment (no medical/paid leave).
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