Distinguished GPU Memory Simulation Architect

Job Title

Distinguished GPU Memory Simulation Architect

Role Summary

This Distinguished Engineer will set technical direction for GPU memory, on-chip interconnect (NoC), and architectural simulation at scale. The role focuses on long-term architecture strategy, simulation methodology, and ensuring modeling investments produce actionable insight for future GPU products.

You will work across GPU architecture, memory, interconnect, software, verification, performance, and product teams, and present clear technical recommendations to senior leaders.

Experience Level

Senior — 18+ years of relevant professional experience.

Responsibilities

Lead strategy, methodology, and cross-team coordination to evaluate and guide GPU memory and NoC architecture.

• Define strategy for next-generation GPU memory and NoC performance and functional models.
• Guide use of simulation, emulation, workload analysis, and AI-assisted model generation to evaluate architectural choices.
• Identify bottlenecks across memory systems, on-chip interconnects, cache hierarchy, data movement, and workloads.
• Translate modeling insights into architecture recommendations, modeling priorities, and product feature direction.
• Establish modeling standards, validation approaches, common workloads, and decision frameworks.
• Collaborate with architecture, memory, interconnect, software, verification, performance, and product teams to align requirements with scalable solutions.
• Communicate trade-offs, risks, assumptions, and expected performance impact to senior technical and business leaders.
• Mentor senior engineers and strengthen modeling and architecture communities.

Requirements

Core qualifications and skills required for success in this role.

• 18+ years of professional experience with a record of setting technical direction for complex architecture, modeling, or simulation systems.
• Deep experience in GPU architecture, including memory systems, cache hierarchy, and on-chip interconnect design.
• Strong performance modeling expertise; experience building, scaling, and validating architectural simulation infrastructure.
• Experience with large-scale software development and strong programming skills in C/C++ and Python or other scripting languages.
• Demonstrated sound judgment in ambiguous technical areas; ability to connect model behavior, workload characteristics, architectural trade-offs, and product requirements.
• Clear communicator with strong technical leadership and experience influencing across multidisciplinary engineering teams.
• Proven mentoring experience and a history of defining architecture strategy or improving simulation methodology.

Nice-to-have:

• Experience in parallel computing, datacenter architecture, large-scale interconnects, or AI/HPC workload analysis.
• Experience building or improving performance modeling frameworks, writing and analyzing large-scale test cases, or using AI tools for model generation, validation, or architectural analysis.

Education Requirements

Bachelor's, Master's, or PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related field — or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.