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NVIDIA

Designs the chips and software that power AI

ASIC Physical Design Engineer New Grad

Silicon & ASIC DesignConfirmed live in the last 24 hours
Full-timeHsinchu, Hsinchu City, TaiwanNo salary listedIn-person

About the Job

Requirements

  • A Master of Science in Electrical Engineering or Microelectronics is required.
  • Project experience in integrated circuit design implementation is required.
  • Coursework in circuit design and digital design is required.
  • Proficient English reading and writing is required.

Responsibilities

  • Perform ASIC physical design from RTL freeze through tape-out, including synthesis, formal verification, constraints definition, timing closure and sign-off, and analysis of process-related timing impacts and methodologies.
  • Integrate chips and generate netlists.
  • Perform synthesis, RTL/netlist quality checks, and formal verification.
  • Create and validate constraints and timing budgets.
  • Work with the ASIC team to analyze and resolve special timing issues and collaborate across teams on chip partitioning and floorplanning.
  • Work with physical implementation engineers to achieve timing closure at partition and full-chip levels.
  • Achieve timing closure for special modes, including I/O, test, clock, and asynchronous modes.
  • Create functional engineering change orders.
  • Develop and improve the timing closure flow from front-end pre-layout through back-end post-layout.
  • Develop flow automation for the areas listed above.
  • Develop methodologies in any of the areas listed above.

Desired Qualifications

  • Hands-on experience with Synopsys EDA software, including Design Compiler, PrimeTime, and Formality, is helpful.
  • Experience with Cadence EDA software, including RC Compiler and LEC, is helpful.
  • Proficiency in Python or TCL is helpful.

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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