Manager, HPC Storage Engineer

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Runpod

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

💰 $20M Seed on 2024-06

Artificial Intelligence • SaaS • B2B

Runpod is a cloud platform that provides on-demand GPU compute and managed infrastructure tailored for AI development and deployment. It offers GPU "Pods" across 31 global regions, serverless GPU endpoints for low-latency inference, multi-node GPU clusters for distributed training, and a hub for deploying open-source models and templates. Runpod emphasizes fast startup (sub-200ms cold starts), autoscaling from zero to thousands of workers, support for 30+ GPU SKUs, and tooling for the full AI lifecycle from experiment to production, targeting developers and enterprise AI teams.

📋 Description

• Own Distributed Storage Architecture: Define, evolve, and operate Runpod’s global storage platforms, supporting training, inference, checkpointing, and dataset access at scale. • Build the Storage Engineering Team: Manage and grow a team of storage and systems engineers. Set clear ownership, technical direction, and operational standards across regions. • High-Performance Shared Filesystems: Design and operate large-scale SAN and NFS deployments, including performance-sensitive shared storage for GPU clusters. • Advanced Filesystems & Platforms: Lead deployments and operations of VAST Data and experience with Lustre or similar parallel filesystems used in HPC and AI environments. • End-to-End Performance Ownership: Drive performance optimization from NAND and NVMe media through controllers, networking, and client access patterns. • Next-Generation Storage Technologies: Evaluate and deploy cutting-edge capabilities such as NFS over RDMA, GPU Direct Storage (GDS), and low-latency data paths for accelerated workloads. • Reliability & Scale: Establish best practices for replication, data tiering, data protection, failure recovery, capacity planning, and lifecycle management. • Automation & Observability: Build automation for provisioning, expansion, upgrades, and monitoring. Ensure deep observability into throughput, latency, and error characteristics. • Cross-Functional Collaboration: Partner with Datacenter Networking, GPU Platform, SRE, and Product teams to ensure storage systems meet evolving workload and customer needs. • Vendor & Partner Management: Own technical relationships with storage vendors, hardware partners, and colocation providers; drive roadmap alignment and issue resolution.

🎯 Requirements

• Engineering Leadership Experience: 3+ years managing storage, systems, or infrastructure engineering teams in production environments. • Distributed Storage Expertise: 8+ years designing and operating large-scale storage systems, including SAN and NFS architectures at multi-petabyte scale. • VAST Data Experience: Hands-on experience deploying, operating, or deeply integrating VAST Data in production environments is required. • Parallel Filesystems: Experience with Lustre or comparable HPC filesystems (e.g., GPFS, BeeGFS) supporting high-concurrency workloads. • Low-Level Storage Knowledge: Deep understanding of NAND, NVMe, PCIe, storage controllers, and performance characteristics across the stack. • High-Performance Data Paths: Proven experience with NFS over RDMA, RDMA-capable transports, or similar technologies. Familiarity with GPU Direct Storage strongly preferred. • Linux Systems Expertise: Strong Linux internals knowledge, including filesystems, I/O scheduling, memory management, and tuning for performance workloads. • Operational Excellence: Experience running 24/7 storage platforms with strong incident response, change management, and post-mortem discipline. • Communication & Leadership: Ability to clearly communicate complex technical tradeoffs and lead teams through high-stakes infrastructure decisions. • Successful completion of a background check.

🏖️ Benefits

• Meaningful equity in a fast-growing company- everyone on the team receives stock options — your impact drives our growth, and you share in the upside. • 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 • Join a passionate team on the cutting edge of AI infrastructure — where culture, learning, and ownership are at the heart of how we scale.