Member of Technical Staff, Data Infrastructure

Make data a solved problem for every GPU workload at Fireworks. We own how data is stored, cached and moved across clouds, so that training and inference teams never have to think about where their data lives or how it gets to them, and no GPU ever waits on it.

In practice, that means building a unified, high-performance data layer that spans parallel file systems, object storage, distributed caches and key-value stores across multiple clouds. Datasets, checkpoints, model weights and KV cache should be in the right place at the right time, at whatever scale the GPUs need. Training jobs start without a data-staging step, inference replicas cold-start without waiting on weight downloads, and the system handles placement, replication and movement on its own.

• Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• 5+ years of experience designing, building and operating storage, caching or data infrastructure in production at scale.