VLSI Physical Design CAD Intern
NVIDIA
VLSI Physical Design CAD Intern
NVIDIA
Designs the chips and software that power AI
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 30 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. We are now looking for VLSI Physical Design (CAD) Engineers.
What you’ll be doing:
Develop in-house tools and solutions
Responsible for flow automation, quality control and performance improvement of NVIDIA VLSI Physical Design flow
Work with EDA vendors on tools evaluation and improvement
What we need to see:
Pursuing MS/PhD in CS/EE
Proficient user of C/C++/Python/Perl is preferred
Basic knowledge of device model, processing technology, timing, noise and power in chip design
Ways to stand out from the crowd:
With analytical ability on placement, routing, timing, clock, power, noise and DFM
Experience on Mathematical algorithm and data structure for VLSI CAD
Hands-on background in EDA software from Synopsys (DC/ICC2/STAR-RC/PT/ICV), Cadence (Genus/Innovus/Quantus/Tempus/PVS), ANSYS (Seahawk/Redhawk) etc is a plus
Hands-on experiences in DL/ML projects/programs is a plus
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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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