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NVIDIA

Designs the chips and software that power AI

Senior Physical Design Interposer Engineer

Silicon & ASIC DesignConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A BS in Computer Science, Electrical Engineering, or a related field, or equivalent experience, is required along with 8 years of flow and methodology development experience building interposer design flows used by engineering teams at scale.
  • Strong programming fundamentals in Python and/or C++, including data structures, algorithms, object-oriented design, and code quality practices are required.
  • Demonstrated experience applying AI/ML techniques in engineering workflows is required, such as using large language models for code generation and debugging, building machine-learning-assisted design analysis tools, or integrating AI-assisted flows into electronic design automation environments.
  • A strong understanding of electrical engineering fundamentals relevant to VLSI interposer design is required, such as signal integrity, power delivery, or parasitic extraction.

Responsibilities

  • Work with interposer engineers to design and develop VLSI flows and methodologies for interposer design.
  • Develop applications that enable project engineers, emphasizing maintainability and ease of use.
  • Develop flows, tools, and methodologies to construct, analyze, and validate interposer designs at multiple stages in the production flow.
  • Optimize the daily workflows of interposer designers.

Desired Qualifications

  • A good understanding of VLSI package design, interposer design, and integrated-circuit physical design is desirable.
  • Strong expertise in developing interposer design flows and methodologies is desirable.

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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