Staff Storage Platform Engineer (AI Storage)
SubmerData Center company
RemoteLead
M&G
Planet First Partners
Norrsken VC
Mundi Ventures
Data & AI
About the role
TL;DR
Design and optimize AI storage architecture for large-scale GPU infrastructure.
- •Design, build, and operate the AI storage layer powering large-scale GPU infrastructure, enabling datasets, model artifacts, checkpoints, and inference state to be delivered to compute clusters with extremely high throughput and predictable latency.
- •Key Responsibilities Design scalable AI storage architectures supporting both edge and core deployments.
- •Define storage strategies for distributed inference, fine-tuning, and training workloads.
- •Architect solutions across multiple storage models: hyperconverged storage, local NVMe storage, and disaggregated AI storage platforms.
- •Requirements Architectural ownership and technical direction.
- •Hands-on execution across storage design, deployment, performance engineering, troubleshooting, platform integration, and operational improvement.
- •Collaboration with compute, networking, and platform engineering teams.
Required skills
Kubernetes
Domain expertise
ai
Tech stack
KubernetesCI/CDDocker