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Server Performance Architect - Hardware

NVIDIA· Architect
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Hybrid (Bengaluru), Hybrid (Hyderabad), Hybrid (Pune), Hybrid (Gurugram)full-timePosted 6mo ago

About the role

NVIDIA seeks architects to drive server-level architectural performance for next-generation AI server systems, combining deep architectural knowledge with hands-on silicon investigations, workload analysis, and tooling development.

Responsibilities

  • Defining and driving server-level performance targets across CPU, GPU, memory, interconnect, networking, and storage subsystems
  • Conducting hands-on workload characterisation and bottleneck analysis on NVIDIA and competitive server platforms using AI training, inference, and HPC benchmarks
  • Leveraging profiling, tracing, and analysis tools to root-cause performance issues and identify optimisation opportunities at the system level
  • Performing trade-off studies on system topology, thermal/power envelopes, and memory hierarchy to guide architectural decisions
  • Collaborating with silicon, platform, firmware, and software teams to identify and close performance gaps from bring-up through production
  • Developing automation and tooling for performance regression tracking and reporting
  • Representing the performance perspective in architecture reviews and cross-functional design discussions
  • Building and maintaining analytical performance models and simulation frameworks for next-generation server platforms
  • Publishing internal performance studies and best-practice guides for partner and customer enablement

Qualifications

  • BS, MS, or PhD in Electrical/Computer Engineering, Computer Science, or equivalent experience
  • 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
  • Strong hands-on experience with system-level profiling and performance analysis tools on server platforms
  • Solid knowledge of GPU-accelerated compute, high-performance networking, or high-performance storage subsystems
  • Proficiency in Python, C/C++, or similar languages for scripting, data analysis, and tool development
  • Comfortable and proficient using AI-powered coding and productivity tools to accelerate analysis, automation, and documentation workflows
  • Excellent communication skills with the ability to distil complex performance data into actionable architectural recommendations

Skills

Required:Server/system performance architectureSystem-level profiling and performance analysisCPU microarchitecture, PCIe/CXL, DDR/HBM, coherencyPython, C/C++Communication
Last updated Sep 11, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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