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Senior CPU Workloads and Simulation Architect

NVIDIA

4 Locations permanent

Posted: April 28, 2026

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Quick Summary

Help improve CPU architectures to support growth in AI, deep learning, HPC, gaming, virtual reality, and autonomous vehicles by designing and implementing simulation mechanisms for complex applications.

Job Description

Do you want to help improve CPU architectures to support growth in AI, deep learning, HPC, gaming, virtual reality, and autonomous vehicles?  Come join the CPU performance architecture team as a Senior CPU Workloads & Simulation Architect and help us push performance boundaries for NVIDIA’s line of CPU products!

What you’ll be doing:

• Research, architect, implement, and evaluate mechanisms for capturing and studying complex applications suitable for architectural and microarchitectural CPU analysis in simulation. This includes multi-core, multi-thread, and heterogenous workloads spanning CPU/GPU/NIC, simulated at the user-level, VM-level, and full-system level.

• Implement tools, processes, and systems for collecting traces and checkpoints for complex multi-threaded heterogeneous applications and support other architects in using those tools to study workloads. 

• Contribute to developing functional and performance models of ARM-based systems. Focus on infrastructure for recording and replaying workload sequences for performance and power analysis.

• Stay on top of guidelines in industry and academia relating to simulation, checkpointing, tracing, deterministic replay, and architectural/microarchitectural analysis of complex heterogeneous computer systems.

What we need to see:

• BS/MS in EE, CE, or CS or equivalent experience

• 12 or more years of relevant experience

• Experience with CPU workload methodology: state capture and replay, trace analysis, SimPoint, etc.

• Knowledge of CPU and system architecture and microarchitecture

• Strong C/C++ and Python programming skills

• Excellent communication and collaboration skills

Ways to stand out from the crowd:

• Strong knowledge in sampling methodology and data science

• Experience with CPU/GPU application development and optimization in Pytorch, TensorFlow, and similar frameworks

• Proficiency in the ARM instruction set architecture

• Experience developing user-mode and/or kernel-mode drivers

• Background in writing functional and/or performance simulators

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 May 2, 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.

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