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Über diese Hardware Systems Engineer - LPU Platform Pathfinding Stelle bei NVIDIA

NVIDIA · Vor Ort · US, CA, Santa Clara

NVIDIA is looking for a Hardware Systems Engineer to join our team and help build next-generation LPU platforms!


These platforms support the most fast-paced AI workloads. This is an outstanding opportunity to work on innovative technology that shapes the AI industry. You’ll collaborate with some of the brightest minds, contribute to system architecture, solve engineering challenges, and strengthen the hardware base for large-scale AI.
 

What you'll be doing:

  • Contributing to hardware development for LPU platforms, investigating architectures for power delivery, cooling, mechanical build, and high-bandwidth interconnects.
  • Supporting system-level technical decisions and trade-off analyses that influence NVIDIA’s LPU roadmap.
  • Working with silicon, architecture, data center, and manufacturing teams to help deliver production-ready systems.
  • Collaborating with vendors to debug issues and drive to resolution.
  • Conducting lab bring-up and hands-on hardware debugging, employing oscilloscopes, logic analyzers, and other bench instruments to analyze and resolve system behavior.
  • Assisting in full-stack system debug, addressing electrical, mechanical, thermal, firmware, and application-level issues.
  • Supporting program execution by tracking issues, contributing to root-cause analysis, and helping drive timely resolution.
     

What we need to see:

  • Bachelor’s degree in Electrical Engineering, Mechanical Engineering, or related field (or equivalent experience).
  • 4+ years of experience in platform, system, or hardware engineering from concept through delivery.
  • Working knowledge in one or more of: electrical/power build, mechanical/thermal engineering, firmware integration, or performance tuning.
  • Practical lab experience with hardware initialization and troubleshooting, including skill with oscilloscopes, multimeters, logic analyzers, and signal measurement instruments.
  • Experience with board building using Cadence tools, including schematic capture (Design Entry HDL/OrCAD/Capture) and PCB layout (Allegro).
  • Experience working in Linux environments to run SW diags, FW upgrades, and retrieve/parse test logs.
  • Understanding of communication protocols such as I2C, SPI, USB and UART.
  • Solid debugging and problem-solving skills across hardware and software boundaries.
     

Ways to stand out from the crowd:

  • Exposure to large-scale AI platforms such as LPU, GPU, TPU, or custom accelerators.
  • Experience supporting the build or validation of accelerator systems at rack or cluster scale.
  • Exposure to advanced system builds such as new power networks, liquid cooling, or optical interconnects.
  • Familiarity with cross-functional collaboration across diverse engineering teams.
     

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/


#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 2, 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.

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NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA .

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