We are looking for research interns to work on foundational areas for coding language models, including pre-training data, mid-training data, synthetic data generation, evaluation, and agentic coding.
Responsibilities * Explore data-centric methods for improving coding LLMs, including data filtering, quality assessment, deduplication, data mixture, and diversity analysis. * Build synthetic data and evaluation pipelines for code generation, code editing, repo-level reasoning, tool use, and multi-step coding tasks. * Run experiments to analyze how data, model, and training strategies affect coding capabilities * Work with large-scale code corpora, developer activity data, and agentic coding trajectories.
Requirements Currently pursuing a phd degree Strong programming skills in Python. Solid understanding of machine learning and large language models. Familiarity with LLM pre-training, mid-training, code models, data curation, evaluation, agents, or tool use. Strong experiment desig...