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NVIDIA

Designs the chips and software that power AI

Manager – ASIC Chip - GPU

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USA

About the Job

Requirements

  • A Bachelor of Science in Electrical Engineering, a Master of Science in Electrical Engineering or Computer Engineering preferred, or equivalent experience.
  • At least 10 years of overall industry experience, including 5 or more years of leadership in GPU or key subsystems.
  • In-depth knowledge of system-on-chip architectures, including central processing unit, graphics processing unit, and memory subsystems.
  • Expertise in silicon process technology, yield analysis, and cost modeling.
  • Proficiency in front-end design flow, microarchitecture, unit partitioning, and pipelining.
  • Proficiency in design verification techniques, tools, and methodologies.

Responsibilities

  • Coordinate all aspects of GPU ASIC development from concept phase to mass production.
  • Engage in architectural definition, silicon process and package selection, performance modeling, power budgeting, register-transfer-level development, and test implementation.
  • Define and track project achievements and dependencies, coordinating activities across intellectual property development, software, emulation, integration, physical development, and very-large-scale integration teams.
  • Collaborate with packaging, system design, design-for-test, test engineering, test software, and chip logistics teams to support silicon bring-up.
  • Identify and mitigate key technical risks to ensure project execution.

Desired Qualifications

  • Proven track record of successfully implementing complex GPU ASIC projects.
  • Demonstrated ability to lead and encourage cross-functional teams.
  • Experience with AI and datacenter products.

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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