Research Engineer, Data Understanding – Foundations

About the role

We are looking to advance how OpenAI builds and understands pre‑training data at scale. In this role you will treat data quality and curation as core research problems, developing new methods to select, combine, and transform data. You will also design rigorous experiments to evaluate how data choices affect model learning and downstream behavior.

Key responsibilities

• Develop novel techniques for data selection, combination, transformation, and quantized representation.
• Create high‑quality datasets that improve model capabilities and support large‑scale model training runs.
• Design and run rigorous experiments to understand the impact of data interventions on model performance.
• Collaborate with frontier model teams and web‑scale data pipelines, translating successful research into scalable processing systems.

Required profile

• Strong track record of new or improved machine‑learning ideas demonstrated through publications, projects, or applied research.
• Ability to own and drive a research agenda from problem selection to impactful outcomes.
• Enthusiasm for OpenAI’s empirical, collaborative research approach.
• Thoughtfulness about AI impact, including privacy, provenance, and data quality (nice to have).