Senior Storage and Networking Product Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine Learning, HPCIndustries

Requirements

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 configuration management/orchestration tools (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

Responsibilities

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
Foster automation in storage and networking operations through the utilization of infrastructure-as-code and orchestration guided by AI/ML

Skills

RDMA

NVMe-over-Fabrics

RoCE

InfiniBand

Ethernet

Distributed Storage

High-Performance Networking

Infrastructure as Code

Orchestration

Capacity Planning

Distributed Filesystems

Parallel Storage

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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