Senior GPU Architect, Performance and Scalability

NVIDIA•Santa Clara, CA

About The Position

This is an outstanding opportunity to join a world-class team at NVIDIA and play a pivotal role in crafting the future of GPU technology. In this role, you will work with dedicated individuals in an inclusive and collaborative environment, driving flawless execution and ambitious projects. NVIDIA is recognized as the world leader in accelerated computing, having pioneered this field to tackle challenges no one else can solve. Their innovative work in AI and digital twins is actively transforming the world's largest industries and profoundly impacting society. NVIDIA is deeply committed to fostering a diverse work environment and proudly operates as an equal opportunity employer, valuing diversity in both its current and future employees. The company ensures non-discrimination in hiring and promotion practices based on various characteristics protected by law.

Requirements

Bachelors/Master’s/PhD in Computer Engineering, Computer Science or related fields (or equivalent experience)
A minimum of 10 years of relevant work experience in GPU or CPU System Architecture development
Proficient programming skills in C++ and Python.
Solid background in Computer Architecture with experience in modeling
Strong communication and interpersonal skills, as well as the ability to thrive in a dynamic, collaborative, distributed team.
Strong problem-solving and debugging skills, with a track record of driving issues to closure

Nice To Haves

Experience with GPU architecture and/or Network-on-Chip (NoC)/Interconnect.
Knowledgeable in system level functions such as reset and boot, DFT.
Consistent track record of efficiently implementing complex architectural features
Outstanding problem-solving skills with a focus on optimizing performance, area, complexity, and power.

Responsibilities

Develop GPU architecture innovations and improvements, optimizing along the axes of scalability/modularity, performance, area, yield, effort, and schedule.
Develop and enhance chip design infrastructure, including functional models and yield simulators, testbench components and analysis tools, to evaluate configurations under different constraints.
Develop tests, test plans and testing infrastructure for new architectures/ features
Work in a matrixed environment, across the different modeling teams, to document, design, develop tools to optimize chip yield and performance
Implement and maintain functional, performance, and yield models
Document architecture specifications; work with ASIC design, software, and VLSI teams to review and explore trade-offs, define solutions, and track progress.
Collaborate with other functional teams (Design, Floorplan, Packaging and Systems Engineering, etc) to validate choices against performance, cost, and scalability targets.
Guide the improvement of functional verification tools and expand other resources to support future GPU architectures