Software Engineer, Pretraining

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code. About the role We’re looking for Software Engineers to build the data systems behind our frontier coding models’ initial training. You’ll work on large-scale crawling, data platform, and pipeline infrastructure, turning raw dumps into the datasets our models train on, and making iteration with researchers fast and reliable. The Data Quality team owns the entire road between raw internet-scale data and the tokens that train frontier models. This team makes sure the right data, in the right form, hits the training clusters on time and at the quality bar required to push the scaling curve. This is done by building our own models, our own high-performance pipelines, and by running the experiments that prove the data is actually stellar. The Data Platform Team owns the infrastructure and pipelines that transform raw data dumps into training-ready datasets. This team improves the speed, reliability, and developer experience of our initial training data pipelines so researchers can quickly experiment with new data sources, quality filters, taxonomies, multimodal data, and data mixes that improve model performance. The Crawling team owns large-scale web crawling and parsing that feeds the top of the funnel for initial training. They discover, schedule, fetch, and parse public web content so high-quality documents become the raw scrapes that Data Quality and Data Platform turn into tokens and mixes. This is deep distributed systems work with real ownership: host coverage and prioritization, fetch success under antibot and trap content, HTML/document parsing quality, and reliability of th