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NVIDIA

Designs the chips and software that power AI

GPU/SOC Low-Power Feature Architect

Hardware Systems IntegrationConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A Bachelor of Science or Master of Science degree in Electrical Engineering or Computer Engineering, or equivalent experience.
  • At least 10 years of work involving capacity, power management, use-case analysis, performance/power modeling, bringup, and/or debugging.
  • Experience in one or more of the following areas: system-level and interconnect power-management optimizations; silicon- and platform-level power modeling for active/idle use cases; or firmware/driver structures and their interaction with hardware.
  • Strong electrical engineering fundamentals and knowledge of computer architecture, high-speed interfaces, timing analysis, process variations, statistical error rates, and power analysis.
  • Track record of influence, leadership, and collaboration across multiple teams toward a unified goal.

Responsibilities

  • Contribute to the design of next-generation high-speed input/output, including NVLink and NVLink-C2C.
  • Optimize input/output power and continue advancing energy efficiency.
  • Ensure interoperability with connected devices and system components in complex interconnect topologies.
  • Investigate technically challenging high-speed input/output bugs and help drive debugging efforts across teams.
  • Work proactively with system architects, mixed-signal and design teams, DGX, software/firmware, hardware/software quality assurance, operations, and application engineering teams to drive design, development, debugging, and release of next-generation 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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