Manager, HPC Storage Engineer

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RunPod

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2022

🤖 Intelligence artificielle

☁️ SaaS

💰 Seed Round en 2024-05

Artificial Intelligence • Cloud Computing • SaaS

RunPod est une plateforme cloud conçue pour faciliter l'entraînement, le perfectionnement et le déploiement de modèles d'IA. Elle propose un cloud GPU distribué mondialement permettant aux utilisateurs de déployer leurs charges de travail d'IA sans effort tout en se concentrant sur la création d'applications d'apprentissage automatique. Avec des fonctionnalités telles que le démarrage rapide des pods, l'autoscaling et la prise en charge de plusieurs frameworks d'apprentissage automatique, RunPod s'adresse aussi bien aux startups, qu'aux institutions académiques et aux entreprises, offrant une solution puissante et économique pour le développement d'apprentissage automatique.

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.

🎯 Exigences

• 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 environments is required. • Experience with Lustre or comparable HPC filesystems (e.g., GPFS, BeeGFS) supporting high-concurrency workloads. • Deep understanding of NAND, NVMe, PCIe, storage controllers, and performance characteristics across the stack. • Proven experience with NFS over RDMA, RDMA-capable transports, or similar technologies. Familiarity with GPU Direct Storage strongly preferred. • Strong Linux internals knowledge, including filesystems, I/O scheduling, memory management, and tuning for performance workloads. • Experience running 24/7 storage platforms with strong incident response, change management, and post-mortem discipline. • Ability to clearly communicate complex technical tradeoffs and lead teams through high-stakes infrastructure decisions. • Successful completion of a background check.

🏖️ Avantages

• 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 — we cover 100% for all employees and partial for dependents. • 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.