Tech Stack
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.
AI @ 4
Deep Learning
GPU @ 4
HPC
Performance Analysis @ 4
PyTorch @ 4
Robotics
System Architecture @ 7
- 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
Help drive the development of CPU technology for architectures used in 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 to advance performance across CPU products.
Responsibilities
- Perform workload bring-up and performance analysis and projection on silicon and full-system simulators.
- Study workloads across AI/DL, CSP, HPC, and autonomous vehicle markets.
- Analyze real-world use cases, identify critical application behavior, and reduce findings to directed test cases.
- Analyze and debug performance-scaling bottlenecks on multicore and multisocket CPU and CPU/GPU systems.
- Collaborate with CPU and interconnect architects to improve future CPU and system designs.
- Benchmark NVIDIA CPU offerings against competing products and recommend software or hardware improvements.
Requirements
- Bachelor's or master's degree in Electrical Engineering, Computer Science, Computer Engineering, or equivalent experience.
- At least 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) is preferred but not required.
Preferred Qualifications
- PhD or research experience.
- GPU driver experience.
- Knowledge of GPU-accelerated workloads and performance modeling for accelerated workloads.
- Experience optimizing AI frameworks such as PyTorch.
Compensation and Benefits
- Base salary for Level 5: USD 224,000–356,500 per year.
- Base salary for Level 6: USD 272,000–431,250 per year.
- Eligible for equity and benefits.
NVIDIA develops accelerated computing technologies for AI, HPC, advanced system design, robotics, autonomous vehicles, healthcare, climate research, and other applications. Its CPU architecture work includes the Grace CPU Superchip and Vera CPU, integrating CPU technology with NVIDIA GPUs and broader systems for AI model training, agentic use cases, data processing, and cloud deployments.
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