About the role
About the projects: we are building LLM evaluation and training datasets to train LLM 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 etc. Main tasks listed: Analyze and triage GitHub issues across trending open-source libraries; Set up and configure code repositories, including Dockerization and environment setup; Evaluating unit test coverage and quality; Modify and run codebases locally to assess LLM performance in bug-fixing scenarios.
Experience
See the official listing for the full requirements.
Selection process
Apply through the official Turing page (free account required). The listing describes this selection process: Two rounds of interviews (60 min technical + 30 min technical & cultural discussion).
Eligibility
India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico (as stated on the listing)