[Hiring] HPC Storage Engineer @Runpod

Role Description

You will be part of the Infrastructure organization, specifically within the team managing Runpod's multi-region storage ecosystem, including:

• Network volumes
• Local NVMe
• S3-compatible object storage

This senior, hands-on group operates in tight coordination with SRE, networking, and supply chain teams, as well as our global hardware partners. The engineers who define our systems also write the code, optimize the fabric, manage on-call rotations, and lead capacity planning.

We're hiring a Senior Storage Engineer to contribute to the design, scaling, and reliability of Runpod's storage platform. This is a hands-on engineering role, not just an administration role. You'll be implementing and maintaining distributed storage deployments, writing the code and automation that operates them.

You will help write what Runpod's storage story looks like for the next several years, including:

• Deciding which distributed storage systems to bet on
• How to tier and place data
• Tuning the network paths storage depends on
• Leading capacity expansions and migrations end to end

Improvements you make will show up immediately as faster cold starts, faster jobs, and fewer incidents for more than a million developers.

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.
• 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, vendor and cloud provider APIs.
• Automate the operations you'd otherwise do by hand.
• Treat infrastructure as code and participate fully in code review, testing, and CI.
• Instrument the storage fleet so its behavior is legible.
• 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.

Qualifications

• 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.
• Self-starting with general direction.
• Continuous improvement mindset.
• Ownership of problems across team boundaries.
• Collaborative and low-ego (but high confidence).

Preferred

• Storage for AI/ML workloads: checkpointing, dataset streaming, model weight distribution, GPU-adjacent data locality, GPUDirect Storage.
• Kubernetes storage internals: CSI drivers, PV/PVC lifecycle, StatefulSets, local persistent volumes.
• Bare-metal and colocation experience: hardware selection, vendor management, firmware, physical failure domains.
• Multi-tenant environments where isolation, fairness, and QoS are hard requirements.
• Experience in a fast-growing cloud or infrastructure provider.

Benefits

• The competitive base pay for this position ranges from ($180,000 - $260,000).
• Meaningful equity in a fast-growing company — everyone on the team receives stock options.
• Generous medical, dental & vision plans.
• Flexible PTO - take the time you need to recharge.
• Most roles are remote work first with an inclusive, collaborative teams utilizing Slack as the main form of internal communication.
• $1,200 Home Office & Equipment Stipend.