RE/RS, Data Understanding - Foundations
This role focuses on advancing how OpenAI builds and understands pretraining data at scale. The individual will treat data quality and curation as core research problems, developing new methods to select, combine, and transform data to improve model capabilities.
About the job
About The Role
We're looking to advance how OpenAI builds and understands pretraining data at scale. You'll treat data quality and curation as core research problems: developing new methods to select, combine, and transform data; creating datasets that improve model capabilities; and designing rigorous experiments to understand how data choices and interventions affect model learning and downstream behavior. You'll work closely with frontier models and web-scale data to build evidence for which approaches work and why, then translate successful research into scalable data processing pipelines
We Expect You To
- Have a strong track record of new or improved ML ideas, through publications, projects, or applied research.
- Own and drive a research agenda, from choosing the right problems to carrying long-running work through to impact.
- Be excited by OpenAI’s empirical, collaborative approach to research.
Nice To Have
- Thoughtfulness about AI’s impact, including privacy, provenance, and data quality.
- Experience building high-performance deep learning or large-scale data processing systems.
Skills
Machine Learning, Data Curation, Data Quality, Deep Learning, Large-Scale Data Processing
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