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We are building LLM evaluation and training datasets to train LLMs 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 other dimensions.
We are looking for experienced software engineers (tech lead level) familiar with high‑quality public GitHub repositories and can contribute to this project. This role involves hands‑on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality.
Commitments Required: At least 4 hours per day and minimum 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)
Employment type: Contractor assignment (no medical/paid leave)