Turing is building LLM evaluation and training datasets to help train LLMs on realistic software engineering problems. This project creates verifiable software engineering tasks from public repository histories using a synthetic, human-in-the-loop approach, while expanding coverage across programming languages, difficulty levels, and task types. The role is for experienced software engineers at a tech-lead level who are familiar with high-quality public GitHub repositories. It involves hands-on software engineering, including development environment automation, issue triaging, and evaluating test coverage and quality. Engineers will work with researchers to identify repositories and issues that challenge LLMs, and may have opportunities to lead junior engineers. The position is fully remote and offered as a contractor assignment. Work commitment options are 20, 30, or 40 hours per week, with at least four hours per day and a minimum four-hour overlap with PST. The contractor assignment does not include medical or paid leave.
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