Staff Engineer, Distributed Storage and HPC & AI Infrastructure

Staff Engineer responsible for architecting and scaling multi-petabyte storage systems for AI training and inference workloads. Key duties include operating high-performance parallel filesystems (Ceph, Weka, Lustre), building Kubernetes-native storage operators, implementing intelligent caching and tiered storage, optimizing KV-cache offload and data paths for GPU clusters, and driving the storage roadmap.

8+ years in storage engineering with multi-petabyte scale. Experience with GPU/HPC clusters for training/inference, including KV-cache offload and model-weight distribution. Deep Kubernetes and cloud-native storage. Strong Go and Python coding. BS/MS in CS or equivalent. Technical leadership in performance, reliability, and cost efficiency. Expertise in parallel filesystems (Ceph, WekaFS, Lustre, Vast), object storage (S3, MinIO), and storage optimization for GPU workloads.