Silicon Reliability Engineer

at Nvidia
USD 108,000-212,800 per year
MIDDLE
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 2 Communication @ 3 JavaScript @ 2 Data Analysis @ 2 Debugging @ 3

Details

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 GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” NVIDIA's GPUs, SOCs, and CPUs are the world leaders in performance and efficiency, and we are continually innovating in creative and unique ways to improve our ability to deliver extraordinary solutions in a wide range of sectors. We want to grow our company and build our teams with the smartest people in the world. Join us at the forefront of technological advancement.

Responsibilities

  • Responsible for GPU and SoC system qualification, including feature checks, system stress at BurnIn conditions, testing of a large number of systems, and debugging issues affecting any unit of the chip or software.
  • Perform validation of reliability stress hardware and software infrastructures and participate in a system-level High-Temperature Operating Life (HTOL) reliability test.
  • Build scripts for automation and data parsing.
  • Deliver silicon aging results for product aging modeling.
  • Drive silicon aging debug meetings and co-work with multi-function teams to root cause it.

Requirements

  • Bachelor’s or Master’s Degree or equivalent in Microelectronics/Electrical/Electronic/Physic or equivalent experience.
  • 3 to 5 years overall experience in semiconductor reliability.
  • Good problem-solving, collaboration, and communication skills.
  • Capability of multi-tasking with priority.
  • Basic knowledge of frequency power thermal constraints and failure analysis techniques.
  • Engineering Experience in system-level debugging and Perf/Power/Speed/Reliability features in CPUs/GPUs/SOCs.
  • Familiarity with scripting languages like Python and/or JavaScript.
  • Good knowledge of board and system design considerations and experience in silicon design/bring-up.
  • An understanding of PC architecture and various commonly used buses.
  • Must be a standout colleague and ready to work with global teams from diverse cultural backgrounds.

Ways to stand out above the crowd

  • Deep understanding of technology and passion for what you do.
  • Familiarity with statistical methods and tools for data analysis.
  • Strong collaborative and communication skills, specifically the ability to effectively guide and influence within a dynamic environment.
  • Strive to be a standout colleague and be ready to work with global teams from diverse cultural backgrounds in a high-energy environment.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

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