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NVIDIA

Hardware Design Validation Engineer - Memory Subsystem

NVIDIA is hiring a Hardware Design Validation Engineer - Memory Subsystem in Santa Clara, United States. It pays $108k-$184k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Little AI ●○○○ is how Level rates this role: aI is not part of the work.
  • Level classes it as a mid-level role.
  • NVIDIA has 2,600+ other open roles on Level.

AI in this role

Widely considered to be one of the technology world’s most desirable employers, NVIDIA is an industry leader with groundbreaking developments in High-Performance Computing, Artificial Intelligence and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization.

NVIDIA’s System Product Team is looking for curious, collaborative, and motivated hardware engineers to take our GPU memory subsystem from first silicon power-on to production.

What you'll be doing:

  • Planning and performing DDR memory tuning, validation, and feature enablement on NVIDIA products.

  • Reviewing silicon design specifications, component datasheets, board schematics, and layout.

  • Exercising your understanding of digital, analog, and computer design to debug and resolve controller, memory, board, or software/firmware level issues at all stages of the product.

  • Refining our memory bringup and validation strategy. Providing feedback and recommendations to silicon, board, and software teams.

What we want to see:

  • BS or MS EE degree with affinity for mixed signal/analog, embedded systems, and digital design (or equivalent experience).

  • 2+ years relevant experience.

  • Understanding of high speed signal integrity and experience with oscilloscopes.

  • Understanding of schematic capture and board design.

  • Working knowledge of PC systems, windows OS, and Linux.

  • Excellent understanding of EE fundamentals. Able to break problems down based on first principles.

  • Familiar with scripting or programming languages such as C, C++, JAVA, Python, or Perl.

  • Possess good collaboration and cross-disciplinary teamwork skills. Comfortable working across time zones.

  • Deeply curious about technology and passionate about learning.

Ways to stand out from the crowd:

  • Experience as a tutor or teacher’s assistant.

  • Good presentation skills.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
108,000 USD – 184,000 USD for Level 2; and 136,000 USD – 212,750 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 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.

How we rate this

Hardware Design Validation Engineer - Memory Subsystem at NVIDIA rates 17 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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