Nvidia Senior Storage Networking Product Engineer 

United States, Texas 

814487971

What you'll be doing:

• Architect, deploy, and maintain distributed storage clusters with a focus on scalable performance and data durability.

• Develop and improve high-performance networking architectures for storage environments, ensuring low-latency data paths for AI/ML and HPC workloads.

• Configure and tune RDMA, NVMe-over-Fabrics, RoCE, InfiniBand, and Ethernet-based fabrics for maximum performance.

• Partner with GPU, networking, and systems teams to ensure seamless end-to-end performance across the full stack.

• Develop automated systems for monitoring, recording, and notifying in storage and networking.

• Build and maintain capacity planning models for network efficiency and storage growth.

• Troubleshoot complex network-storage interactions, including bottlenecks in distributed filesystems, parallel storage, and interconnects.

• Implement data protection and compliance controls such as encryption in-transit, access control, and auditing. and foster automation in storage and networking operations through the utilization ofinfrastructure-as-codeand orchestration guided by AI/ML.

What we need to see:

• BS/MS in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

• 12+ years of experience in storage systems engineering, production infrastructure, or large-scale data center operations.

• Deep knowledge of networking protocols and technologies: TCP/IP, Ethernet, InfiniBand, RDMA, RoCE, NVMe-oF, Fibre Channel.

• Hands-on experience with high-performance storage systems: Lustre, GPFS, Ceph, distributed object storage, enterprise SAN/NAS.

• Expertise in Linux systems engineering, including tuning, performance analysis, and debugging.

• Skilled in coding/scripting using Python, Bash, Go, or C/C++ to automate, monitor, and optimize performance.

• Experience with configurationmanagement/orchestrationtools (Ansible, Terraform, Puppet, Chef, Kubernetes).

• Familiarity with observability stacks (Prometheus, Grafana, Elastic, InfluxDB) to monitor and optimize storage and network performance.

• Proficient in recognizing and resolving complex system bottlenecks within storage and networking layers.

Ways to Stand Out from the Crowd:

• Experience crafting and operating RDMA-accelerated HPC/AI clusters at scale, with hands-on expertise with network topologies and large-scale switch/router deployments.

• Familiarity with network telemetry, packet capture tools (sFlow, NetFlow, Wireshark, and proven history of capacity planning and optimizing performance for distributed storage systems over high-speed networks.

• Background in jointly developing storage networks for AI/ML training pipelines, large-scale inference, and RAG workflows.

• Proficiency in hybrid cloud storage and networking solutions (like Kubernetes CSI, cloud-native fabrics, and hybrid on-prem/cloud setups).

• Contributions to open-source networking or storage projects.