Staff Engineer, Distributed Storage and HPC & AI Infrastructure

📋 Description

• Architect and implement storage roadmap and high-performance architecture for scaling GPU fleet.
• Scale multi-petabyte AI/ML storage; integrate Vast, Weka, Ceph; auto tiering.
• Develop intelligent caching and tiered storage for extreme IOPS and GPU-scale throughput.
• Tune storage isolation at L2/L3 networks for secure multi-tenant storage.
• Code Kubernetes storage operators and controllers for automated provisioning and quotas.
• Aim for 10+ GB/s per GPU node; design multi-tier caching; scale across thousands of nodes.

🎯 Requirements

• 8+ years in storage engineering, managing distributed storage at multi-petabyte scale
• Proven track record deploying and operating high-performance storage for GPU/HPC clusters
• Deep Kubernetes and cloud-native storage experience in production environments
• Strong coding skills in Go and Python with production-grade systems and tooling
• BS/MS in Computer Science, Engineering, or equivalent practical experience
• History of technical leadership: designing systems that significantly improved performance, reliability (99.999%+ uptime), or cost efficiency

🎁 Benefits

• Competitive compensation, startup equity, health insurance, and benefits.
• Flexible remote work options.