Principal AI Memory Systems Architect
$250k - $300kCyberCoders
Job Description
Job Description
Principal AI Memory Systems Architect
Job Title: Principal AI Memory Systems Architect
Location: San Jose, CA or Irvine, CA
Compensation: $250K - $300K base plus equity
Requirements: AI Systems Architecture, Memory Hierarchy, CXL, HBM, AI Inference, Computer Architecture, Memory Disaggregation, Processing-in-Memory (PIM), GPU / Accelerator Architecture, ASIC/SoC Architecture
We are a leading provider of high-performance modular memory subsystems and next-generation storage-class memory solutions. We specialize in cutting-edge technologies that enable innovation in AI, cloud computing, and enterprise infrastructure. Our product portfolio includes DDR4/DDR5 DIMMs, NAND-based SSDs, and advanced interconnect technologies such as CXL and PCIe .
RoleThis is a senior architecture role for someone who understands how AI workloads translate into memory, bandwidth, latency, compute, interconnect, power, and system-level requirements. The role partners closely with the Chief AI Systems Architect, AI Product Strategist, AI Software Architect, and R&D teams to develop next-generation AI hardware and memory architectures.
We are particularly interested in investigating opportunities involving:- AI memory hierarchy evolution for larger models and context windows
- HBM, DDR, CXL, storage, and memory-tiering strategies
- Near-memory and processing-in-memory architectures
- Reducing data movement, power consumption, and system cost
- Expanding effective memory capacity and utilization
- New hardware architectures that outperform current AI systems
Key Responsibilities
- Architect AI systems, memory subsystems, and accelerator platforms
- Translate AI workload requirements into memory, compute, bandwidth, and latency specifications
- Design solutions leveraging HBM, DDR, CXL, memory pooling, disaggregation, caching, and persistent memory
- Analyze architectural tradeoffs across performance, power, capacity, area, and cost
- Characterize AI workloads including LLM inference, RAG, agentic AI, long-context inference, and KV-cache management
- Evaluate emerging technologies such as CXL memory expansion, memory compression, and near-memory computing
- Partner with software teams to optimize runtime, memory management, scheduling, and workload orchestration
- Build architectural models, simulations, benchmarks, and proof-of-concept prototypes
- Define product architectures, technical roadmaps, and system specifications
- Conduct technical due diligence on startups, technologies, IP, and M&A opportunities
Required Qualifications
- BS/MS in Electrical Engineering, Computer Engineering, Computer Science, or related field (PhD preferred)
- 10+ years in computer architecture, memory systems, semiconductor design, AI hardware, or related fields
- Deep expertise in memory hierarchy and computer architecture
- Experience with HBM, DDR, CXL, PCIe, UCIe, high-speed interconnects, and/or AI accelerators
- Strong understanding of AI/ML workloads and architectural tradeoffs
- Demonstrated experience developing complex semiconductor or computing systems
- Proven ability to translate system requirements into hardware architectures and specifications
Preferred Experience
- LLM inference and transformer architectures
- KV-cache systems and AI inference runtimes (e.g., vLLM)
- CUDA/GPU architectures
- CXL 2.x/3.x, memory pooling, and memory disaggregation
- Processing-in-memory and near-memory computing
- AI networking and storage-class memory
- ASIC/SoC architecture, RTL, and microarchitecture
- Hardware/software co-design and architectural modeling
- Edge AI systems
Benefits
- Vacation/PTO
- Medical
- Dental
- Vision
- Equity
- 401k w/ match
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