Are you looking for an SOC Methodology Engineer opportunity? If yes, come and join us. The complexity of the chip has greatly increased over the years. We are now packing hundreds of billions of transistors in a chip to meet the growing computing demand in a footprint that is responsible to our environment. The NVIDIA System-On-Chip (SOC) group is looking for a top ASIC Methodology Engineer with a curiosity about SOC design automation, RTL integration, and chip build and assembly. You should have real passion for methodologies and automation solutions that enable SOC creation in the most optimized way. In this position, you will get the opportunity to face the challenge in building the complex GPU and Tegra chips and have chances to use cutting edge technology to solve those challenges. You will also have chances to interact directly with Physical Design, CAD, Package Design, Software, DFT and other teams.
What you'll be doing:
Padring related methodology including tool development and RTL design verification.
Define and develop system-level methodologies and tools to build SOCs in an efficient and scalable manner
Using AI to solve SOC Design related challenges
What we need to see:
MS in Computer or Electrical Engineering or equivalent experience
3+ years of proven experience in chip design, specializing in SOC integration and methodology
Excellent analytical and problem-solving skills
Experienced script skills: Perl, Python, or other industry-standard scripting languages.
Great communication and teamwork skills to interact within the team and across functional teams to build consensus
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.
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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