Turing is building LLM evaluation and training datasets for 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 and difficulty levels. 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 engineering work, including development environment automation, issue triage, and evaluating test coverage and quality. The engineer will assess how LLMs perform on real code and collaborate with researchers on challenging repositories and issues. There may also be opportunities to lead a team of junior engineers. This is a fully remote contractor assignment. The available time commitments are 20, 30, or 40 hours per week, with at least four hours per day and four hours of overlap with PST. The assignment does not include medical benefits or paid leave.
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