Senior Network Validation Engineer at NVIDIA

Santa Clara, California, United States

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI, DatacenterIndustries

Requirements

M.S. degree in Engineering/Computer Science/related field (or equivalent experience)
10+ years of experience
Over 5 years of proven experience in Software Quality Engineering and Network Testing, including significant contributions to QA strategies and test documentation
Strong skills in Python (preferred) or other scripting languages like Perl, Shell and hands-on experience with Jenkins or similar CI/CD based pipelines
Strong technical abilities, problem solving, designing, coding and debugging skills
Extensive hands-on experience in configuring and troubleshooting data center networking, including Layer 2/Layer 3 protocols such as VLAN, BGP, EVPN, and spine-leaf topology; InfiniBand networks experience desired
Experience with using test tools from Ixia or Spirent and working experience in test management
Hands-on experience working on Unix or Linux based OS
Great team player with multi-tasking ability and good interpersonal & documentation skills
Solid foundation in and understanding of software engineering practices
Excellent design, debugging and problem-solving skills, with a strong bias for action, quality and engineering excellence

Responsibilities

Design validation plans from bare metal to at scale data center integration tests
Debug, triage issues, perform root cause analysis, verify fixes, define new tests, and improve product test plans
Configure, administer, troubleshoot, and oversee the qualification of Ethernet and InfiniBand networks in large-scale datacenter environments
Perform server function & network validations including Ethernet & InfiniBand protocol & system level reliability test end to end application tests
Design, develop, and maintain automation frameworks and test automation suites, including automated reporting, while consistently increasing end-to-end automation coverage with each release cycle
Track and coordinate all validation activities from bring up to production release
Collaborate with multi-functional teams including application teams, HW designers, networking team, FW, security etc. to debug any HW/SW product issues
Provide inputs to architecture teams for next generation Data Center networking design

Skills

Network Validation

Ethernet

InfiniBand

Debugging

Root Cause Analysis

Automation

Scripting

Datacenter Integration

Bare Metal Testing

Troubleshooting

Network Administration

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.

Land your dream remote job 3x faster with AI

Try Jobo Free