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NVIDIA

Designs the chips and software that power AI

Lead Post-Silicon Validation Engineer

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A bachelor's or master's degree in Electrical Engineering, Computer Engineering, or a related field, or equivalent experience.
  • At least 12 years of proven experience, including three years working with memory systems in the lab.
  • Direct experience taking a system-on-chip or GPU from concept to production.
  • Experience with DRAM and high-speed DRAM interfaces such as HBM, GDDR, and LPDDR, including their timing, analog, and digital requirements.
  • Ability to understand the most important issues across a large volume of data.
  • Ability to facilitate decisions by considering all relevant perspectives.
  • Strong written, verbal, and technical communication skills.

Responsibilities

  • Manage and help lead post-silicon bring-up, characterization, and productization of memory systems for GPU products.
  • Develop, qualify, and support compliance of memory-system software and firmware.
  • Serve as the primary contact for internal and external customers and DRAM vendors regarding silicon issues related to memory.
  • Contribute throughout the GPU development cycle, from concept, Plan of Record, architecture, microarchitecture, design, validation, physical design, and tape-out.
  • During the pre-silicon phase, work with design and verification teams to define features required for smooth bring-up and productization.
  • During the post-silicon phase, bring the GPU from initial power-on through production.

Desired Qualifications

  • Experience working with DRAM vendors to debug post-silicon issues and drive solutions.
  • A proven record of implementing processes and methodologies.
  • SystemC or C++ development skills, or relevant programming experience.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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