Senior GPU Memory Architect

NVIDIA•Us, CA

About The Position

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. We are seeking a world-class computer architect to contribute to the development of future high-performance GPU computing systems. Ideal candidates will have a strong track record of understanding and analyzing memory systems architecture to improve performance, power, and area (PPA). A broad perspective across the field of CPU/GPU architecture and depth in the area of PPA analysis is highly desirable. This position offers the opportunity to have a real impact in a fast paced, technology-focused company!

Requirements

Bachelor’s degree (or equivalent experience) in Computer Engineering, Electrical Engineering, Computer Science, or a related field with a minimum of 8+ years of relevant professional experience is required. Or an MS degree with 6+ years or a PhD with 4+ years of experience are also eligible.
An understanding in CPU or GPU architecture, memory systems, or network on-chip design.
Experience in large-scale SW development projects and strong programming skills in C/C++ and Python or other scripting languages.
Excellent communication skills, both written and verbal, for effective collaboration with internal teams and external partners.

Nice To Haves

Background in parallel computing, datacenter architecture, or large scale interconnect architecture.
Expertise in data analysis and visualization using tools such as pandas and related technologies.
Experience in writing, running, and analyzing test cases within performance modeling frameworks.
Experience in using AI tools for code development, validation, and analysis.

Responsibilities

Define and architect innovative features for next-generation GPU memory and on-chip interconnect subsystems.
Develop, implement, and refine performance models to evaluate architectural choices and predict subsystem behavior.
Develop and evaluate test cases to validate performance models and ensure robust feature integration.
Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations.
Collaborate closely with multi-disciplinary engineering teams to translate product requirements into architectural solutions.