Server Performance Architect - Hardware

Job Title

Server Performance Architect - Hardware

Role Summary

The Server Performance Architect will define and drive system-level performance targets for next-generation AI server platforms. The role focuses on hands-on workload characterization, system-level profiling, and cross-functional collaboration to close performance gaps from bring-up through production.

Work spans CPU, GPU, memory, interconnect, networking, and storage subsystems and includes developing automation and tools for performance regression tracking and reporting.

Experience Level

Senior - 10+ years of experience in server or system performance architecture or related disciplines.

Responsibilities

Key responsibilities include performance analysis, tooling, and architectural guidance:

• Define and drive server-level performance targets across CPU, GPU, memory, interconnect, networking, and storage.
• Characterize workloads and perform bottleneck analysis using AI training, inference, and HPC benchmarks on NVIDIA and competitive platforms.
• Use profiling, tracing, and analysis tools to root-cause performance issues and identify optimization opportunities.
• Perform trade-off studies on system topology, thermal/power envelopes, and memory hierarchy to guide decisions.
• Collaborate with silicon, platform, firmware, and software teams to identify and close performance gaps through production.
• Develop automation and tooling for performance regression tracking and reporting.
• Represent performance considerations in architecture reviews and cross-functional design discussions.
• Build and maintain analytical performance models and simulation frameworks for next-generation server platforms.
• Publish internal performance studies and best-practice guides for partner and customer enablement.

Requirements

Core technical skills and experience required; additional desirable qualifications follow.

Must-have

• 10+ years of experience in server/system performance architecture or related disciplines.
• Deep understanding of modern server architectures: CPU microarchitecture, PCIe/CXL, DDR/HBM memory subsystems, and coherency protocols.
• Hands-on experience with system-level profiling and performance analysis tools on server platforms.
• Knowledge of GPU-accelerated compute, high-performance networking, or high-performance storage subsystems.
• Proficiency in Python, C/C++, or similar for scripting, data analysis, and tool development.
• Strong communication skills to distill complex performance data into actionable architectural recommendations.
• Proficient using AI-assisted coding and productivity tools to accelerate analysis, automation, and documentation.

Nice-to-have

• Experience with AI/ML training and inference workloads at data-center scale.
• Familiarity with NVIDIA GPU architectures (Hopper, Blackwell, Rubin) and associated software stacks such as CUDA and NCCL.
• Background in chip-to-chip interconnect performance analysis (C2C, UCIe).
• Exposure to power/thermal-aware performance optimization techniques.
• Track record of published performance studies or conference contributions.

Education Requirements

BS, MS, or PhD in Electrical/Computer Engineering, Computer Science, or a related technical 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.