Senior Physical Design Engineer
NVIDIA
Senior Physical Design Engineer
NVIDIA
Designs the chips and software that power AI
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 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. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA is looking for best-in-class Senior Physical Design Engineers to join our outstanding Networking Silicon engineering team, developing the industry's best high speed communication devices, delivering the highest throughput and lowest latency! Come and take a part in crafting our groundbreaking and innovating chips, enjoy working in a meaningful, growing and professional environment where you make a significant impact in a technology-focused company.
What you'll be doing:
You will lead all aspects of physical design and implementation of SOC devices targeted at the networking markets.
Work will be at the partition and chiplet level.
As a member of a team, you will participate in establishing physical design methodologies, flow automation, chip floorplan, power/clock distribution, chip assembly and P&R, timing closure.
Daily work involves all aspects of physical chip development (RTL2GDS) – trial synthesis, power and clock distribution, place and route, timing closure, power and noise analysis and physical verification.
What we need to see:
BSEE / MSEE or equivalent experience.
5 years of experience in VLSI physical design implementation on 5nm, 4nm and 3nm technology.
A successful track record of delivering designs to production is a requirement.
Able to assist in design flow development and debugging, including application of ML/AI solutions.
Already a validated strong power user of P&R, Timing Analysis, Physical Verification, IR Drop Analysis, CAD tools from Synopsys (ICC2/DC/PT/STAR/ICV), Cadence (Genus/Innovus/Tempus) and other major EDA companies.
Confirmed prior experience in timing closure, clock/power distribution and analysis, RC extraction and correlation, place/ route and tapeout solutions.
To be successful you should possess strong analytical and debugging skills.
Proficiency using Python, Perl, Tcl, Make scripting is helpful.
Great teammate
NVIDIA is widely considered to be the leader of AI computing, and one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.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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