HPC Storage Engineer - West Coast

Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod to experiment, train, fine-tune, deploy, and scale AI on one platform. The platform has processed more than 20 billion inference requests. We closed a $100M Series A in June 2026. We're at an inflection point for AI infrastructure, and we're building the platform the next generation of developers will depend on.

We're a small, remote-first team. We take ownership seriously, move fast, and ship work that more than a million developers rely on every day. We're looking for people who care deeply, build with urgency, and want to matter at scale.

You will be part of the Infrastructure organization, specifically within the team managing Runpod's multi-region storage ecosystem, including network volumes, local NVMe, and S3-compatible object storage. At Runpod, storage is a critical, high-impact resource; it determines cold start velocity, training job data streaming efficiency, and the reliable persistence of model weights and checkpoints.

Responsibilities

• Own capacity, durability, availability, and performance characteristics of network volumes, local NVMe, and S3-compatible object storage.
• Tune the full I/O path: device and filesystem configuration, caching and read-ahead strategies, replication and erasure coding trade-offs, and client-side mount behavior.
• Diagnose hard performance problems end to end.
• Lead capacity expansions, hardware refreshes, migrations, and rebalances without customer-visible disruption.
• Work with Runpod and partner networking teams to design and tune the network paths storage depends on: high-throughput east-west fabric, MTU and jumbo frames, congestion and flow control, multipath, and NIC/offload configuration.
• Understand and optimize RDMA/RoCE and high-speed IB/Ethernet fabrics as they apply to storage traffic.
• Write production code (Go, Python, or similar) for storage control-plane services, provisioning workflows, data movement pipelines, and monitoring.
• Build against and extend APIs: our own control plane, S3-compatible interfaces, CSI drivers, Kubernetes APIs, and vendor/cloud provider APIs.
• Treat infrastructure as code and participate fully in code review, testing, and CI.
• Instrument the storage fleet so its behavior is legible: IOPS, throughput, latency, error and retry rates, capacity utilization, and per-tenant consumption.
• Build dashboards, SLOs, and alerts that catch degradation before customers do.
• Participate in an on-call rotation for storage systems and drive blameless post-incident follow-through.

Requirements

• 8+ years in infrastructure, storage, or systems engineering, with substantial ownership of production storage at scale.
• Deep, practical experience with at least one distributed storage system — Ceph, MinIO, Lustre, GPFS/Spectrum Scale, MooseFS, WekaFS, VAST, ZFS-based systems, or comparable.
• Strong Linux internals and storage-stack knowledge: block layer, filesystems, NVMe, page cache, I/O schedulers, NFS/SMB, iSCSI/NVMe-oF.
• Building and/or operating S3-compatible object storage services.
• Solid networking fundamentals with specific experience tuning networks for storage workloads.
• Proficiency in writing and shipping production code in Go, Python, Rust, or similar.
• Hands-on experience with observability tooling (Prometheus, Grafana, Datadog, or equivalent).
• A track record of performance analysis and debugging under real production pressure.
• Strong self-direction and ownership.