A key part of NVIDIA's strength is to innovate and deliver the highest performance in the world for AI and accelerated computing. We are constantly looking for ways to improve our GPU architecture and maintain our leadership. NVIDIA is seeking a motivated system architect to define future aspects of our GPU through employing pioneering technologies. Your role will be cross-disciplinary, working with software, ASIC design, verification, physical design, VLSI and platform teams. Our system architects excel at pushing the state of the art while making the best engineering trade-offs.
What you will be doing:
Develop GPU architecture innovations and improvements, optimizing along the axes of scalability/modularity, performance and power efficiency, area, yield, effort, and schedule.
Benchmark GPU configurations (core count, memory and interconnect bandwidth) employing advanced packaging; identify optimal designs for future data center workloads.
Develop and enhance architecture analysis infrastructure, including performance simulators, testbench components and analysis tools, to evaluate configurations under different constraints.
Implement and maintain high-level functional and performance models. Analyze application workloads and performance simulation results to identify areas of architecture improvements.
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 packaging choices against performance, cost, and scalability targets.
What we need to see:
Master’s/PhD in Computer Engineering, Computer Science or related fields (or equivalent experience)
A minimum of 8 years of relevant work experience in GPU or CPU System Architecture development
Proficiency in data analysis (Python, Excel) to correlate configuration changes with performance metrics.
Deep understanding of accelerated computing and AI data center requirements and tradeoffs, including performance bottlenecks, TCO, Power Delivery Network (PDN), DC Networking, etc
Strong communication and interpersonal skills, as well as the ability to thrive in a dynamic, collaborative, distributed team.
Ways to stand out from the crowd:
Experience with GPU architecture, especially in off-chip IO, memory subsystem, and/or Network-on-Chip (NoC)/Interconnect. Knowledgeable in system level functions such as reset and boot, DFT, and power management
Expertise in analyzing performance scaling and bottlenecks at device and system levels for AI/accelerated computing workloads
Knowledgeable in modern packaging technologies, and their costs and benefits
Consistent track record of efficiently implementing complex architectural features
Outstanding problem-solving skills with a focus on optimizing performance, area, complexity, and power
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 a diverse 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.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.”
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