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17 часов назад

SoC Memory Subsystem Architect (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Текст:
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TL;DR
SoC Memory Subsystem Architect (AI): Designing unified memory space architectures and microarchitectures for Baidu AI accelerator SoCs with an accent on system fabrics, caches, coherency, MMUs, and distributed AI training systems. Focus on simulating and optimizing memory subsystem performance, analyzing workloads, and debugging functional and performance issues from high-level models through post-silicon validation.

Location: Sunnyvale, California, United States; onsite at hirify.global’s Sunnyvale office

Company

hirify.global develops AI silicon and systems, including AI accelerator SoCs.

What you will do

  • Provide technical leadership across phases of AI SoC development, primarily designing unified memory space architecture.
  • Develop architecture and microarchitecture for SoC fabrics, system caches, system coherency, and MMUs.
  • Define and build unified memory space systems across distributed AI training systems with software and SoC design teams.
  • Collaborate with hardware design, verification, emulation, and validation teams to build and test architecture, performance, and functionality.
  • Simulate features, analyze benchmarks and workloads, and identify microarchitecture optimizations.
  • Debug performance and functional issues using high-level models, RTL simulation, and silicon.

Requirements

  • 10+ years of experience in silicon architecture or IP design focused on memory subsystems.
  • Strong understanding of distributed AI training system requirements for SoC memory subsystems.
  • Experience with digital hardware design, CPUs or hardware accelerators, and/or peripheral design.
  • Knowledge of software and operating-system requirements for memory systems.
  • Experience with system performance analysis and debugging in pre-silicon and/or post-silicon environments.
  • Background in system interconnects, system MMUs, caches, memory technologies such as HBM, GDDR, DDR, and LPDDR4/5, data analysis, and a Master’s or PhD in Electrical or Computer Engineering. Excellent communication skills in both English and Chinese are required.

Culture & Benefits

  • Work in small, fast-moving teams focused on ambitious AI hardware goals.
  • Self-directed environment for motivated professionals.
  • Opportunities to learn new skills and grow.
  • Collaborative, team-oriented working style.

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