About The Position

NVIDIA has continuously reinvented itself over two decades. Our 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today! Working at the Silicon Co-design Engineering Team at NVIDIA, you will be responsible for productizing NVIDIA's chips into groundbreaking consumer, professional, server, mobile, and automotive solutions. The qualified candidate should be comfortable in a lab environment and should demonstrate a passion towards creation, execution and improvement of silicon validation plans.

Requirements

  • Completing a BS or MS degree in EE, CE, Systems Engineering or equivalent experience.
  • Problem solving, debugging, analysis and logical reasoning skills with examples to prove it.
  • Understanding of digital design, circuit analysis, algorithms, computer architecture, BIOS, drivers, and software applications.
  • Strong programming skills in one or more of Python, JavaScript, C/C++

Nice To Haves

  • Familiarity with statistical methods, tools for data analysis, and analyzing large datasets to draw actionable conclusions, possibly applying deep learning techniques.
  • Knowledgeable in signal integrity, timing analysis, fault analysis, sampling, computer architecture, filters.
  • Familiar with lab tools (oscilloscopes and logic analyzers).
  • Experience in Database and Web Development is a plus!

Responsibilities

  • Develop and implement methodologies to characterize silicon and validate system features on pre-production silicon.
  • Drive root-causes analysis efforts of hardware failures through lab experimentation and collaboration with other teams within NVIDIA.
  • Find innovative solutions to sophisticated silicon and system level problems to productize silicon and refine future designs to fine-tune architected features post-silicon.
  • Analyze workloads like DL/AI, AAA games, Adobe Suite, and Video Conferencing to understand how we can push market leading energy efficiency.
  • Characterize pre-production silicon fabricated using innovative processes for speed, performance, power, yield, and quality to draw correlation to design.
  • Design or commission tools on evaluation platforms to automate and optimize characterization, data collection, test case execution, and results analysis.
  • Analyze workloads to achieve best-in-class energy efficiency and evaluate the return and investment of new techniques and features, including use case benefit and design-for-productization.
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