Senior Product Engineer - Datacenter

Posted 15 Days Ago
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Santa Clara, CA, USA
In-Office
108K-213K Annually
Mid level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Launch NVIDIA AI supercomputing platforms into mass production by collaborating with NPI and manufacturing teams, defining system-level manufacturing tests, optimizing assembly lines and test stations, qualifying alternate components, and improving yield, throughput, quality, cost, and DPPM. Analyze production data and conduct lab experiments to resolve yield and test issues, ensure signal-integrity requirements, update BOMs, and support customer escalations.
Summary Generated by Built In

We are now looking for a Senior Datacenter Product Engineer! NVIDIA Corporation is a world leader in visual computing technology. The GPU, which the company invented, serves as the visual cortex of modern computers and is at the heart of their products and services. NVIDIA has transformed into a specialized platform company that targets four large markets – Gaming, Professional Visualization, Datacenter and Automotive – where visual computing is essential and deeply valued. Their work also uncovers new universes to explore and enable amazing creativity and discovery by powering what was once thought to be science fiction inventions like artificial intelligence and autonomous cars.

Collaborating with your peers across various engineering groups, you will successfully launch new NVIDIA AI Supercomputing Platforms to production. These purpose-built systems bring together the full power of NVIDIA GPUs, NVIDIA NVLink and NVIDIA InfinBand networking. With its end-to-end performance and flexibility, NVIDIA HGX and DGX enable researchers and scientists to combine simulation, data analytics, and AI to drive scientific progress. This product family represents the company’s fastest growing line of business as well as its largest total available market opportunity. We are looking for a product engineer with system architecture and GPU technology knowledge to support new GPU hardware in mass production. Your responsibilities will include planning and establishing processes, defining test requirements and optimizing the production line to deliver new GPU boards. You will also be instrumental in helping the team to achieve the desired cost and quality metrics considered best-in-class.

What you will be doing:

  • Collaborate with NPI teams for smooth production ramp at worldwide manufacturing sites as you continuously find opportunities for potential process improvements and collaborate with multi-functional teams to implement.

  • Recommend, drive and ensure compliance to DFx requirements for robust signal integrity performance as related to layout, mechanical components, assembly procedures, etc.

  • Develop and deliver test specs for system level manufacturing screens for all new products to meet the required HW coverage, quality and product requirements for various business units.

  • Drive alternate components qualifications and BOM updates

  • Collaborate with CM to define product assembly line, number of test stations and number of assembly fixtures, optimized for cost and throughput.

  • Craft creative solutions and workarounds through volume data analysis and lab experimentation to solve challenging yield and test problems seen on the production floor.

  • Lead optimization and continuous improvement efforts on the production screen spec definition processes to minimize waste and meet test time, yield, DPPM requirements.

  • Support customer facing and quality teams during customer escalations to understand the issue and fix gaps identified in coverage.

What we need to see:

  • BS or MS degree in EE/CE/IE/ME or equivalent experience.

  • 8+ years of relevant industry experience.

  • Strong engineering fundamentals. Knowledge and experience in GPU and/or CPU development, design, system architecture, as well as key technologies such as high-speed interconnects, memories (HBM, GDDR, etc.), system reliability, and server RAS features

  • Knowledgeable in statistics, timing analysis, and fault analysis.

  • Strong communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills.

  • Must be able to work independently with minimal direction and drive projects in an efficient and effective manner.

Ways to stand out from the crowd:

  • Prior board/system level electrical design experience.

  • Mass production experience.

  • Track record of continuous process improvement with a passion for tools and automation.

With competitive salaries and a generous benefits package, NVIDIA is widely regarded as one of the most sought-after employers in the technology sector. We have some of the most thoughtful and dedicated individuals across the globe working for us. Due to unprecedented growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we would love to connect with 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 168,000 USD - 258,750 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 14, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

Skills Required

  • Bachelor’s or master’s degree in electrical engineering, computer engineering, industrial engineering, mechanical engineering, or equivalent experience
  • 3 or more years of relevant industry experience
  • Strong engineering fundamentals
  • Knowledge of GPU and/or CPU development, design, and system architecture
  • Experience with high-speed interconnects and memories such as HBM or GDDR
  • Knowledge of system reliability and server RAS features
  • Knowledge of statistics, timing analysis, and fault analysis
  • Strong communication and organizational skills
  • Ability to work independently with minimal direction and drive projects efficiently
  • Prior board or system-level electrical design experience
  • Mass production experience
  • Track record of continuous process improvement and interest in tools and automation

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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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