NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel.

The NVIDIA GPU and SoC Architecture group is seeking strong architects with great analytical skills and a deep understanding of system architecture and performance to use your skills creatively on processor and system architecture performance of full applications driving scalable improvements for all of our artificial intelligence/machine learning, automotive, geforce and high-performance computing products. This position offers you the opportunity to have a real impact on the hardware and software that underlies the most exciting trends in modern computing in the world. We are looking for someone who is passionate about and loves what you do and excited about creatively applying what you know to make a difference.

What you'll be doing:

Performance analysis/ bottleneck analysis of complex, high performance GPUs and System-on-Chips (SoCs).
Work on hardware models of different levels of extraction, including performance models, RTL test benches and emulators to find performance bottlenecks in the system.
Work closely with the architecture and design teams to explore architecture trade-offs related to system performance, area, and power consumption.
Understand key performance usecases for the product. Develop workloads and test suites targeting graphics, machine learning, automotive, video, compute vision applications running on these products.
Drive methodologies for improving turnaround time, finding representative data-sets and enabling performance analysis early in the product development cycle.
Develop required infrastructure including performance simulators, testbench components and analysis tools.

What we need to see:

BE/BTech or MS/MTech, or equivalent experience in relevant area, PhD is a plus.
2+ years of relevant experience dealing with system level architecture and performance issues.
Strong understanding of System-on-Chip (SoC) architecture, graphics pipeline, CPU architecture, memory subsystem architecture and Network-on-Chip (NoC)/Interconnect architecture.
Solid programming (C/C++) and scripting (Bash/Perl/Python) skills. Exposure to Verilog/System Verilog, SystemC/TLM is a strong plus.
Strong debugging and analysis (including data and statistical analysis) skills, including use of RTL dumps to debug failures.
Exposure to performance simulators, cycle accurate/approximate models or emulators for pre-silicon performance analysis is a plus.
Excellent communication and organization skills.
Ability to work in a global team environment.

Ways to stand out from the crowd:

Strong background in System Level Performance aspects for Graphics and High Performance Computing.
Exposure to GPU application programming interfaces like CUDA, OpenGL, DirectX.
Expertise in data analysis and visualization.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA leads the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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