Software Engineer, Data Infrastructure

Design, build, and operate the distributed storage system that feeds model training and evaluation.

Run this system multiple on Kubernetes clusters at petabyte scale.

Work with researchers and training-infra teams on how jobs actually read and write data, and turn that into throughput, latency, and durability requirements

Work through the networking, I/O, and consistency problems of moving large datasets and checkpoints across regions and backends, with GPU idle time and time-to-insight as the measures of success

You may be a good fit if you have:

Strong storage fundamentals, including replication, consistency, caching, and data lifecycle management.