Director of Memory Design
Acceler8 · acceler8talent.com
San Francisco CountyDirector15–20 yrs
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The job in short
A director-level full-time Electrical / Electronics Engineer role at Acceler8 in San Francisco County, asking for 15–20 years of experience. Skills mentioned: VLSI, SOC.
VLSISOC
Details
- Found
- 6 d ago · posted 2026-11-04
- Location
- San Francisco County, California
Full description
Director of Memory Design
Acceler8 Talent is partnering with a startup designing a cutting-edge 3D-memory-integrated AI accelerator platform to hire an experienced, visionary Director of Memory Design.
In this role, you'll architect and implement a custom memory controller. You'll own the access path from memory requests to data delivery, extending an existing controller for custom requirements.
What You'll Do:
• Own custom controller architecture and SystemVerilog RTL from design through SoC integration and tapeout.
• Design memory-access pipelines and low-latency paths; evaluate scheduling, queue depth and bandwidth/latency/power tradeoffs.
• Adapt controller functions such as scheduling, ECC, refresh, training and power management to interface requirements.
• Optimize custom DRAM/3D-memory connectivity, collaborating with memory partners on TSV fabrics and interface requirements.
• Drive lint, CDC/RDC, equivalence, synthesis, constraints and timing convergence with physical-design and verification teams.
• Define/review verification plans, maintain technical documentation and mentor engineers.
What You Bring:
• Direct memory-controller or substantial memory-subsystem architecture and RTL-design ownership.
• Strong DDR/LPDDR/GDDR understanding and deep memory request/data-pipeline reasoning. SystemVerilog, front-end convergence and scripting; multiple successful silicon tapeouts.
• Ability to make concrete VLSI tradeoffs and debug complex timing and structural design issues.
• 15-20 years of relevant experience; hands-on technical leadership is central.
• HBM2/2E/3 base-die design, custom DRAM interfaces and 3D/TSV integration. C
• ontroller performance modeling, scheduler evaluation and queue-depth analysis.
• AI inference memory patterns, CXL and multi-die/chiplet integration.
• Low-power techniques and high-speed memory-interface DFT.
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