Senior GPU Memory Architect

NVIDIA is seeking a world-class computer architect to contribute to the development of future high-performance computing systems, with a focus on enhancing the power-constrained performance of the hardware.

Ideal candidates will have a strong track record of understanding and analyzing memory systems architecture to improve performance per watt (perf/W) and performance per millimeter (perf/mm).

A broad perspective across the field of computer architecture and depth in the area of power, performance, and area (PPA) analysis is highly desirable.

NVIDIA has pioneered programmable GPUs and the CUDA language and is a world leader in high-performance computing technology, with aggressive plans for future processors.

This position offers the opportunity to have a real impact in a fast-moving, technology-focused company.

What you will be doing:

Develop innovative high-performance processor and system architectures, focusing on the memory system and energy efficiency.

Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$.

Develop and enhance architecture prototype models for power and noise analysis.

Participate in performance and power simulation of features to analyze, define, and improve energy per byte.

Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations.

Debug power, performance, and functional issues with high-level models, RTL simulation and emulation, silicon, and systems.

Collaborate with outside partners on system infrastructure.

What we want to see:

10+ yrs of experience in CPU/GPU architecture, memory systems design with a focus on energy efficiency in the system.

Bachelors in Electrical Engineering, Computer Science, or related field (or equivalent experience).

Expertise in power analysis and modeling in pipeline-based architectures.

Good understanding of power analysis tools like Ansys Power Artist, Synopsys PTPX, etc.

with C, C++, and some scripting languages.

Ways to stand out from the crowd:

MS/PhD in Electrical Engineering, Computer Science, or related field

Experience with hardware design languages such as Verilog or VHDL

Prior experience in developing and optimizing algorithms for power efficiency

Demonstrated ability to innovate and drive continuous improvement in system architecture

Excellent communication skills, both written and verbal, for effective collaboration with internal teams and external partners.

You will also be eligible for equity and benefits.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.