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Samsung Semiconductor is seeking an industry-leading SSD Storage and System Architect with recognized technical influence to design and define our next-generation Enterprise, Datacenter (DC), and AI-optimized storage architectures. As AI/ML workloads explode, storage has become the primary bottleneck for data ingestion, checkpointing, and GPU utilization. This role focuses on the end-to-end design of high-performance storage systems, optimization of flash translation layers (FTL), and hardware-software co-design engineered specifically to accelerate AI training and inference. You will leverage your deep domain expertise to align system architecture with major hyperscale cloud vendor AI clusters while directly bridging the gap with Samsung's internal R&D teams to maximize the competitive edge, silicon efficiency, and performance synergy of Samsung's cutting-edge memory, CXL, and controller solutions.

Location: Daily onsite presence at our San Jose headquarters in alignment with our Flexible Work policy with 10% of domestic travel.

Reports to: Principal Engineer, R&D Product Development Planning

What You’ll Do

AI-Optimized Architecture Design: Define and model enterprise/DC SSD architectures optimized for massive parallel read paths required by AI data loaders (e.g., PyTorch, TensorFlow) and high-burst write paths for AI model checkpointing.
Samsung Product Integration: Translate complex hardware, CXL, and controller constraints into optimized firmware architectures for Samsung’s enterprise SSD controller, FTL, and NAND flash subsystems.
Cloud Infrastructure Alignment: Architect features tailored for hyperscaler AI infrastructure, matching specifications like Microsoft’s Azure AI Cloud storage architectures and Meta’s next-generation GPU-accelerated storage platforms.
HW/FW Co-Design: Collaborate closely with ASIC design, firmware development, and validation teams to resolve cross-domain architectural bottlenecks in ultra-low latency environments.
Technology Prototyping: Develop architectural simulators or FPGA prototypes to evaluate next-generation storage features, AI caching algorithms, and host-managed storage paradigms.
Industry Influence & Innovation: Leverage an established technical network to align emerging system architectures with broader storage industry trends, open-source AI ecosystems, and storage standards (NVMe, OCP, SNIA).
Strategic IP Creation: Drive the creation of foundational architectural patents in the domains of AI storage optimization and near-data processing to protect Samsung's system-level intellectual property.
Hyperscale AI Engagement: Jointly architect next-generation AI datacenter deployment models (e.g., custom pooling, disaggregated storage, GPUDirect Storage [GDS] integrations, and Ethernet-attached SSDs) directly with lead architects from AWS, Google Cloud, Microsoft, and Meta.
Advanced Feature Pioneering: Lead the architectural definition of advanced storage paradigms such as FDP (Flexible Data Placement), ZNS (Zoned Namespaces), and computational storage specifically tailored to offload AI data-preprocessing tasks.

What You Bring

Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field with 10+ years experience, or a Master's degree with 8+ years experience, or a PhD with 5+ years experience.