Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Performance Optimization @ 4
System Architecture @ 7
PyTorch @ 4
GPU @ 4
Deep Learning @ 4
AI @ 4
HPC @ 4
Performance Analysis @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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? Join the CPU performance architecture team and help push performance boundaries for NVIDIA's CPU products.
Responsibilities
- 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, gaming, virtual reality, and autonomous vehicles.
- Study real-world use-cases, 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 findings.
- Benchmark NVIDIA’s CPU offerings against competition and suggest software or hardware improvements.
Requirements
- 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.
Company & context
NVIDIA is a global leader in accelerated computing, delivering breakthroughs in AI, HPC, and advanced system design. With the introduction of the Grace CPU Superchip, and the announcement of the Vera CPU, NVIDIA has expanded into the CPU server market to complement GPUs and SoCs. These CPUs play a critical role in orchestrating complex workloads with exceptional performance-per-watt efficiency, integrating with NVIDIA's broader technology stack to enable faster AI model training, efficient data processing, and scalable cloud deployments.
Compensation & other details
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 is an equal opportunity employer. The company does not discriminate 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.