Job description

Do you want to help drive the development of CPU technology for architectures used for artificial intelligence (AI) / deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming, virtual reality, and autonomous vehicles? Come join the CPU performance architecture team and help us push performance boundaries for all our CPU products! What you'll be doing: • Work on workload bring-up and performance analysis/projection, both on silicon and full-system simulator. • Study workloads for a wide range of markets, including AI/DL, CSP, HPC, and autonomous vehicles. • Study real world use-cases and identify critical application behavior and reduce to directed test cases. • Analyze and debug performance scaling bottlenecks on multi-core and multi-socket CPU and CPU/GPU systems. • Work with CPU and interconnect architects to improve future CPU and system designs based on your findings. • Benchmark NVIDIA’s CPU offerings against competition and suggest software or hardware improvements. What we need to see: • BS/MS in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience. • 12+ years of relevant experience. • Experience with CPU workloads and performance analysis. • Knowledge of performance test development and benchmarking for CPU and I/O. • Deep knowledge of CPU microarchitecture and system architecture. • Experience with the ARM instruction set architecture (ISA) preferable but not required. Ways to stand out from the crowd: • PhD or Research experience. • GPU driver experience. • Knowledge of GPU-accelerated workloads and modeling performance of accelerated workloads. • Experience with performance optimization of AI frameworks such as PyTorch. NVIDIA is a global leader in accelerated computing, delivering breakthroughs in AI, HPC, and advanced system design. Our technologies power transformative applications across industries — from robotics and autonomous vehicles to healthcare and climate research. With the introduction of the Grace CPU Superchip, and more recently, the announcement of the Vera CPU, NVIDIA has expanded into the CPU server market, complementing our world-class GPUs and SoCs. These CPUs play a critical role in orchestrating complex workloads with exceptional performance-per-watt efficiency. The CPU architecture team is driving innovations that integrate seamlessly with NVIDIA’s broader technology stack, enabling faster AI model training, agentic use-cases, efficient data processing, and scalable cloud deployments. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until April 12, 2026. 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.

Requirements

Must-haves

Work on workload bring-up and performance analysis/projection, both on silicon and full-system simulator.
Study workloads for a wide range of markets, including AI/DL, CSP, HPC, and autonomous vehicles.
Study real world use-cases and identify critical application behavior and reduce to directed test cases.
Analyze and debug performance scaling bottlenecks on multi-core and multi-socket CPU and CPU/GPU systems.
Work with CPU and interconnect architects to improve future CPU and system designs based on your findings.
Benchmark NVIDIA’s CPU offerings against competition and suggest software or hardware improvements.
BS/MS in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience.
12+ years of relevant experience.
Experience with CPU workloads and performance analysis.
Knowledge of performance test development and benchmarking for CPU and I/O.
Deep knowledge of CPU microarchitecture and system architecture.
Experience with the ARM instruction set architecture (ISA) preferable but not required.
PhD or Research experience.
GPU driver experience.
Knowledge of GPU-accelerated workloads and modeling performance of accelerated workloads.
Experience with performance optimization of AI frameworks such as PyTorch.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until April 12, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

Platform: eightfold
Effort: medium