• Design and optimize high-performance data pipelines for distributed training and storage (using tools like Arrow, DuckDB, LanceDB, BigQuery, vector databases). • Focus on low-level optimizations (latency, throughput, reliability, GPU usage). • Build monitoring and visualization tools for tracking data quality, pipeline performance, and experiments. • Optimize distributed AI workloads for reliability, latency, and efficiency. • Scope and supervise projects so that interns, PhD students, and post-docs can contribute and collaborate effectively. • Support recruiting efforts and help shape the growth of the infrastructure team.