Manager, HPC Storage Engineer

Stack

Responsibilities

• ▹Define, evolve, and operate Runpod's global storage platforms, supporting training, inference, checkpointing, and dataset access at scale
• ▹Build and manage a team of storage and systems engineers, setting clear ownership and technical direction
• ▹Design and operate large-scale SAN and NFS deployments, including performance-sensitive shared storage for GPU clusters
• ▹Lead deployments and operations of VAST Data and Lustre or similar parallel filesystems
• ▹Drive end-to-end performance optimization from NAND/NVMe media through controllers, networking, and client access patterns
• ▹Evaluate and deploy next-generation storage technologies such as NFS over RDMA and GPU Direct Storage
• ▹Establish best practices for replication, data tiering, data protection, failure recovery, and capacity planning
• ▹Build automation and observability for provisioning, expansion, upgrades, and monitoring
• ▹Collaborate with Datacenter Networking, GPU Platform, SRE, and Product teams
• ▹Own technical relationships with storage vendors, hardware partners, and colocation providers

Requirements

• ▹3+ years managing storage, systems, or infrastructure engineering teams in production environments
• ▹8+ years designing and operating large-scale storage systems, including SAN and NFS architectures at multi-petabyte scale
• ▹Hands-on experience deploying, operating, or deeply integrating VAST Data in production
• ▹Experience with Lustre or comparable HPC filesystems (e.g., GPFS, BeeGFS) supporting high-concurrency workloads
• ▹Deep understanding of NAND, NVMe, PCIe, and storage controller performance characteristics
• ▹Proven experience with NFS over RDMA or RDMA-capable transports; familiarity with GPU Direct Storage strongly preferred
• ▹Strong Linux internals knowledge: filesystems, I/O scheduling, memory management, and performance tuning
• ▹Experience running 24/7 storage platforms with strong incident response and change management discipline
• ▹Ability to clearly communicate complex technical tradeoffs and lead teams through high-stakes decisions
• ▹Successful completion of a background check

Nice to have

• ▹Experience supporting AI training pipelines, large-scale model checkpointing, and dataset streaming workloads
• ▹Familiarity with RDMA fabrics and close collaboration with datacenter networking teams
• ▹Experience designing storage systems for multi-tenant isolation and secure data access
• ▹Background in hyperscale, HPC, or AI-focused infrastructure environments
• ▹Experience building internal storage platforms or abstractions consumed by product teams

Soft skills

What we offer

• ▹Competitive base pay of $150,000-$240,000 USD depending on experience and location
• ▹Meaningful equity in a fast-growing company
• ▹Generous medical, dental & vision plans
• ▹Flexible PTO
• ▹Remote-first role with Slack as the main internal communication channel

About the company

Founded in 2022, Runpod is a fast-growing, well-funded, remote-first company providing cloud infrastructure for full-stack AI applications, with a team spread across the US, Canada, and Europe.