Design multi-petabyte AI/ML storage systems
Integrate WekaFS, Ceph, Lustre, etc.
Lead capacity planning and cost optimization
Design/optimize RDMA, InfiniBand, 400GbE networks; tune for max throughput/min latency; implement
Build Kubernetes storage operators/controllers; enable automated provisioning, self-service
Deliver 10-50 GB/s per GPU node; optimize caching (weights/datasets/checkpoints), parallel

🎯 Requirements

8+ years in storage engineering with 3+ years managing distributed storage at multi-petabyte scale
Proven track record deploying and operating high-performance storage for GPU/HPC clusters
Deep Kubernetes and cloud-native storage experience in production environments
Strong coding skills in Go and Python with demonstrated ability to build production-grade tools
BS/MS in Computer Science, Engineering, or equivalent practical experience
History of technical leadership: designing systems that significantly improved performance

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