ASIC Verification Engineer
NVIDIA
ASIC Verification Engineer
NVIDIA
Designs the chips and software that power AI
We are now looking for a ASIC Verification Engineer. NVIDIA SOC System-ASIC team is hiring a senior verification engineer. In this role, you will work closely with Arch, design and verification engineers to thoroughly verify some top-level related control units (like: Fuse/Floorsweep, Strap, Reset, Sysctrl) and some silicon measurement related units from unit-level to fullchip-level. Those units are important IPs used in both NVIDIA GPU and Tegra products.
What you’ll be doing:
Micro-architecture definition for System-level modules (Fuse, Strap, Floorsweep, In-silicon measurement, Reset, Sysctrl, etc...)
Unit-level and System-level verification for System-level modules.
Own some NVIDIA internal checks to guarantee the design quality.
What we need to see:
BS / MS or equivalent experience in electrical / computer engineering and related.
Above 2 years of ASIC design/verification experience.
Familiar with verification methodology, tools and flow.
Understand frontend ASIC design flow including RTL design, synthesis and timing analysis.
Excellent analytical and problem-solving skills.
Fluent English (both written and spoken) and excellent communication skills.
Good team work spirit, easy to cooperate with team members.
Ways to stand out from the crowd:
Broad knowledge with Video techniques, SOC architecture and Computer architecture is a big plus.
Strong programming skills in C/C++, SystemVerilog, Perl and Python is appreciated as a plus.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people on the planet working for us. If you're creative and autonomous, we want to hear from you!
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.
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