Owner of developer-facing content and reference pipelines for ML training data workflows. Produce cookbooks, benchmarks, demos using real datasets, advocate internally for developer needs, answer user questions, and represent the company at conferences and workshops.

Design and implement low-level, high-performance storage and cloud-scale data infrastructure for ML domains, focusing on OS-level systems programming, performance engineering, data layouts, compression, and orchestration. Work onsite in NYC or London.