Staff Engineer, Distributed Storage,HPC & AI Infrastructure

<h3><strong>About the Role</strong></h3> <p>In this role, you will design and deliver multi-petabyte storage systems purpose-built for the world’s largest AI training and inference workloads. You’ll architect high-performance parallel filesystems and object stores, evaluate and integrate cutting-edge technologies such as WekaFS, Ceph, and Lustre, and drive aggressive cost optimization-routinely achieving 30-50% savings through intelligent tiering, lifecycle policies, capacity forecasting, and right-sizing.&nbsp;</p> <p>You will also build Kubernetes-native storage operators and self-service platforms that provide automated provisioning, strict multi-tenancy, performance isolation, and quota enforcement at cluster scale. Day-to-day, you’ll optimize end-to-end data paths for 10-50 GB/s per node, design multi-tier caching architectures, implement intelligent prefetching and model-weight distribution, and tune parallel filesystems for AI workloads.&nbsp;</p> <p>Hybrid Working 2 days a week at our offices in Amsterdam</p> <p><strong>Responsibilities</strong></p> <ul> <li>Design multi-petabyte AI/ML storage systems; integrate WekaFS, Ceph, etc.; lead capacity planning and cost optimization (30-50% savings via tiering, lifecycle policies, right-sizing).</li> <li>Design/optimize RDMA, InfiniBand, 400GbE networks; tune for max throughput/min latency; implement NVMe-oF/iSCSI; troubleshoot bottlenecks; optimize TCP/IP for storage.</li> <li>Build Kubernetes storage operators/controllers; enable automated provisioning, self-service abstractions, multi-tenant isolation, quotas; create reusable Helm/Terraform patterns.</li> <li>Deliver 10-50 GB/s per GPU node; optimize caching (weights/datasets/checkpoints), parallel filesystems, and data paths; troubleshoot with profiling tools; scale to thousands of nodes.</li> <li>Build multi-tier caches (local NVMe, distributed, object); optimize data locality and model-weight distribution; implement smart prefetching/eviction.</li> <li>Implem