NVIDIA is seeking capable customer-facing hardware engineers to work directly with Cloud Scale Providers (CSP’s) deploying next generation AI-centric Data Centers. The HW Systems Engineer is front-and-center in deploying next generation Nvidia MGX platforms, such as Grace-Blackwell and Vera Ruben NVL72 racks, at our largest customers.
As AI continues to evolve into the era of reasoning, Data Centers focused solely on AI, known as AI Factories, are vital to scale compute and networking infrastructure needed for agentic AI processing. The CSP HW Systems Engineer is the central point of contact for the team of Applications Engineers deploying these AI Factories. The ideal candidate is proactive, customer friendly, and able to lead large cross-functional teams to debug highly complex problems. The CSP Systems Engineering team is deploying the latest generation racks, so close collaboration with architecture and NPI engineering teams is required.
What you’ll be doing:
Collaborate with major cloud service providers (CSP), their OEM/ODM’s, and internal teams to help deploy the latest Nvidia Vera-Ruben AI rack’s
Work with other domain expert teams at NVIDIA to ensure customer solutions are optimized for the highest performance servers in the world
Solve deep server system technical issues at the hardware, software and application level, ensuring customer success and time to market
Act as the central point of contact between CSP customers and Nvidia architecture teams to develop future GPU-accelerated data center architectures and roadmaps
Excellent verbal, written communication, and technical presentation skills in English.
Up to 30% travel expected
What we need to see:
Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, or a related field (or equivalent experience).
5+ years of proven experience in system-level design and integration of server products from concept to deployment.
Solid understanding of x86 server architecture, PCIe, DDR, Infiniband and high-speed interconnects
Basic understanding of BMC (Baseboard Management Controller) architecture, I2C (SMBus), power management and system telemetry controls
Familiarity with Linux OS and command line experience
Knowledge of the latest PCIe Gen5 and Gen6 technical interface challenges
Strong problem-solving and analytical skills as well as excellent communication and teamwork skills
Strong analytical, problem-solving, time-management, and organizational skills, with the ability to manage multiple complex initiatives in dynamic environments.
Ways to stand out from the crowd:
Self-motivated and eager to learn.
Can work under high pressure and dynamic environments.
In-depth understanding of CPU, GPU, Networking and architectural tradeoffs is a plus!
A desire to understand technology deeply.
Can communicate and explain clearly information relevant to your audience.
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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