System Power & Performance Architect, Datacenter AI

NVIDIA Gruppe

Santa Clara (CA)

Hybrid

USD 232,000 - 368,000

Full time

4 days ago
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Benefits offered by this job

Equity
Benefits package
Hybrid work model

Job summary

NVIDIA is seeking a senior system architect specialized in power and performance optimization for datacenter and HPC platforms. You will shape multi-generation roadmaps, own power management strategies, and drive boot/IST architectures across complex IP ecosystems.

You will influence decisions across architecture, ASIC, board, and firmware teams, aiming to improve power/performance trade-offs while delivering scalable solutions for AI workloads.

Qualifications

  • 15+ years of system architecture and validation experience with power/perf optimization.
  • Experience guiding architecture decisions that shipped across silicon programs.
  • Deep knowledge of HSIO power management and boot flow architectures.

Responsibilities

  • Define multi-generation roadmap for system-level power and performance features.
  • Own architecture for HSIO power management, DVFS, P-states, and low-power features.
  • Lead system-level boot and IST architecture across multi-IP systems.
  • Drive power management strategy at datacenter scale, including rack-level telemetry.
  • Identify and redesign system-level processes to meet new product requirements.
  • Serve as technical authority across architecture, ASIC, board, and firmware teams.

Skills

Power management
DVFS
P-states
System boot flows
Low-power design
Datacenter scale architecture

Education

BS/MS in EE/CE

Job description

NVIDIA is seeking a senior system architect specialized in power and performance optimization for datacenter and HPC platforms. You will shape multi-generation roadmaps, own power management strategies, and drive boot/IST architectures across complex IP ecosystems.

You will influence decisions across architecture, ASIC, board, and firmware teams, aiming to improve power/performance trade-offs while delivering scalable solutions for AI workloads.

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