AI Memory Solution Architect

What you'll do

• Analyze and develop AI memory and storage architectures, including memory and cache controllers and system interconnects.
• Create system-level modeling and simulation environments and deliver memory subsystem and IP designs, including specifications, RTL, verification, and FPGA prototypes.
• Optimize memory systems for performance, power efficiency, and scalability; maintain technical specifications, documentation, and test plans.

What they ask for

• MS in Electrical and Computer Engineering or a related field, with 8+ years of hardware design experience focused on SoCs and memory subsystems; or Ph.D. with 4+ years.
• Strong understanding of computer architecture, memory systems, and hardware design.
• Expertise in digital design, including microarchitecture specifications, system modeling, RTL design, synthesis, timing closure, and PPA analysis.
• Problem-solving, complex system software debugging, communication, and cross-functional collaboration skills.

Nice to have

• Working knowledge or experience with simulation frameworks such as QEMU, Gem5, and DRAMPower, and other relevant open-source simulators.
• Familiarity with DRAM, HBM, NVMe, CXL, and PCIe.

Pay

$155,000 — $255,000 USD (salary range; pay type not specified)

Tools

QEMU, Gem5, DRAMPower, DRAM, HBM, NVMe, CXL, PCIe

AI focus

Develops memory and storage solutions and energy-efficient AI/ML computing infrastructure.