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NVIDIA

Designs the chips and software that power AI

Senior SoC Subsystem and 1/O Architect - Lpu

Silicon & ASIC DesignConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
  • At least 8 years of proven experience in SoC architecture, subsystem architecture, I/O architecture, interconnect architecture, GPU/CPU architecture, accelerator architecture, or high-performance systems.
  • Strong understanding of SoC architecture and uncore subsystem development.
  • Extensive understanding of I/O and interconnect cores including PCIe, CXL, NVLink, NVLink-C2C, UCIe, AXI, CHI, or NoC fabrics.
  • Experience working from product requirements to architecture requirements and IP/subsystem specifications.
  • Experience crafting functional models, architectural models, golden models, or C/SystemC models from architecture specifications.
  • Solid grasp of memory ordering, coherency, address translation, interrupts, virtualization, MMUs/IOMMUs, enumeration, configuration, and error management.
  • Solid knowledge of boot, reset, firmware handoff, capability discovery, security, RAS, debug, and power-management architecture.
  • Strong communication abilities and capability to harmonize architecture decisions across IP, firmware, software, verification, and product groups.

Responsibilities

  • Define high-level SoC subsystem architecture for LPU products.
  • Convert LPU product requirements into architectural specifications for uncore, I/O, memory, firmware-facing, boot, reset, safety, fault-tolerance, diagnostic, and power-regulation subsystems.
  • Collaborate with IP teams to develop detailed build documents for PCIe/CXL, NVLink/NVLink-C2C, UCIe, AXI/CHI, NoC fabrics, memory controllers, coherency blocks, MMUs/IOMMUs, boot, reset, and associated SoC infrastructure.
  • Specify subsystem behavior encompassing enumeration, capability discovery, configuration flows, sequence control of memory operations, data consistency, address mapping, interrupt handling, virtualization, error handling, and firmware/software-visible controls.
  • Build or guide functional and architectural models from specifications using C++, SystemC, Python, or similar languages.
  • Use models to validate architecture intent, subsystem behavior, configuration sequences, and IP interactions before RTL or silicon is available.
  • Drive tradeoffs across bandwidth, latency, power, area, timing, scalability, reliability, security, debuggability, and software usability.
  • Review IP specifications, subsystem architecture documents, model behavior, verification plans, and validation strategies.
  • Collaborate with architecture, IP, firmware, software, RTL, verification, platform, and post-silicon teams to bring architecture decisions to completion.

Desired Qualifications

  • Hands-on experience with LPU, GPU, CPU, AI accelerator, chiplet, or multi-die SoC architecture.
  • Extensive knowledge in PCIe/CXL, NVLink/NVLink-C2C, UCIe, AXI/CHI, coherent fabrics, NoCs, or chip-to-chip links.
  • Extensive knowledge in formulating architecture specifications for advanced SoC subsystems.
  • Experience building executable functional models directly from product, architecture, or protocol specifications.
  • Understanding of deep learning workloads, numerics, memory architecture, and bandwidth/latency tradeoffs.
  • Experience with boot architecture, reset sequencing, secure boot, RAS, debug, DFT, power sequencing, or post-silicon validation.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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