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NVIDIA

Designs the chips and software that power AI

Director Reliability Hardware System

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A B.Sc. or M.Sc. in Materials Science and Engineering.
  • At least 15 years of overall demonstrated management experience with teams of 10 or more.
  • At least 8 years of management experience.
  • Ability to multitask across many assignments and coordinate testing for numerous programs.
  • Deep understanding of physics of failure and reliability physics related to semiconductors, printed circuit board assemblies, and interconnects, including electromigration, stress-induced voiding, and thermal fatigue.
  • Hands-on experience with failure analysis techniques such as cross-sectioning, scanning electron microscopy/energy-dispersive X-ray spectroscopy, CSAM, X-ray, and dye-and-pry to identify root causes at the material and structural level.
  • Proficiency in reliability statistics, including Weibull analysis, accelerated life testing, and mean time between failures modeling.
  • Comprehensive knowledge of industry standards such as JEDEC, IPC, and Telcordia for component- and system-level qualification.

Responsibilities

  • Lead end-to-end reliability and failure analysis activities for the Networking organization and serve as the primary advocate for product stability and long-term performance.
  • Direct multiple system-level teams; coach, mentor, and develop engineering managers; conduct performance evaluations; and scale the organization’s capabilities.
  • Collaborate with Board Build, Mechanics, Thermal, PCB Layout, and Production teams to ensure a broad approach to quality.
  • Drive high-priority investigations into complex, intermittent field failures, using advanced failure analysis techniques to determine root causes.
  • Use statistical tools and physics-of-failure models to predict product life cycles and identify potential wear-out mechanisms before they reach the field.
  • Influence product architecture from the beginning by incorporating Build for Reliability and Build for Manufacturing requirements into initial hardware specifications, or apply equivalent experience.
  • Formalize a lessons-learned process so failure analysis results inform design rules for next-generation networking hardware.
  • Define new processes to improve coverage and overall product quality.

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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