The NVIDIA SOC System-ASIC team is looking for a Infrastructure and Methodology engineer with an interest in developing new tools and optimizing existing design flow & process to improve design work efficiency and quality. The ideal candidate for this position needs to have strong programming skills, communication skills, and broad ASIC design/verification knowledge.
SOC System-ASIC team focuses on developing some System/Top-level related control and measurement units and features, like: Fuse/Strap, Floorsweep, Reset, ISM and Sysctrl. Those units are important functions in all NVIDIA products. You will have opportunities to understand the details of those functions and the detailed NVIDIA working flow & process about how to deliver those functions successfully. The design of those functions becomes more and more complex therefore to fully verify those implementations and ensure bug-free within the tight schedule becomes more and more challenging. So the Infrastructure and Methodology work are more and more important. Your mission is cooperating with talents inside SOC System-ASIC team and NVIDIA infrastructure team to develop some innovative and groundbreaking tools, working flow & processes to improve whole team design efficiency and quality.
What you’ll be doing:
Be involved in some design work for the IPs and features owned by System-ASIC team
Brainstorm with IP design owners to figure out suffering points or discuss infra-related improvement ideas. Settle down the specific requirement and choose the suitable methodology to develop infrastructure flow/tool
Responsible for Reset methodology work, include: utilize in-house or industry commercial tool and flow to guarantee reset design quality, develop new tool or flow to improve reset design quality and efficiency
What we need to see:
MS in EE/CE/CS
2+ years of design or design methodology experience
Strong coding skill for Python, Perl, TCL, JavaScript etc.
Understand ASIC design/verification flow and have experience for CDC/RDC/Synthesis/Timing closure
Fluent English (both written and spoken) and excellent communication skills to interface with many groups and build consensus
Ways to stand out from the crowd:
Good team work spirit, easy to cooperate with team members
Has Web system, Database knowledge is a plus
Knowledge on deep-learning experience is a plus
Top Skills
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.”
