Principal Engineer, AI System Architect (Hardware)

Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. Advancing the World’s Technology Together Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities. Job Title: Principal Engineer, AI System Architect (Hardware) The Architecture Research Lab (ARL) focuses on addressing fundamental system-level bottlenecks in modern AI, particularly in memory capacity/bandwidth and system-scale communication . By leveraging Samsung’s world-class memory technologies, ARL explores and defines next-generation AI system architectures that deliver step-function improvements in performance, efficiency, and scalability. We are seeking a Principal AI System Architect who will play a Technical Lead role in bridging AI workloads, system architecture, and hardware design . In this role, you will develop system-level performance models, drive architecture-level design decisions, and propose forward-looking AI system architectures that shape Samsung’s long-term AI platform strategy. Location : Daily onsite presence at our San Jose office in alignment with our Flexible Work policy Job ID : 42852 What You’ll Do Technically Lead the architecture team with strong direction, shaping system‑architecture strategy and advancing key innovations Conduct system-level architectural research for next-generation AI systems, spanning compute, memory, and interconnect/network subsystems. Develop and maintain analytical and simulation-based system modeling frameworks to evaluate AI workloads and identify performance, scalability, and efficiency bottlenecks at rack- and system-scale. Analyze representative and emerging system-level architectural research (e.g., LLMs, DLRMs, and future AI models) to derive architecture requirements and trade-offs across compute, memory, networking, and power. Drive architecture-level design decisions through quantitative modeling, design-space exploration, and performance/power projections. Perform comparative studies of alternative system architectures, reporting performance and performance-per-watt metrics to guide strategic technology choices. Collaborate closely with cross-functional teams in hardware architecture, memory, interconnect, and system engineering to align modeling insights with implementation realities. Communicate architectural insights and recommendations through clear technical presentations and documentation. Occasional domestic and international travel (<10%). What You Bring Ph.D. in Computer Science, Electrical Engineering, or a related field preferred, with 15+ years of experience in system architecture for large-scale computing platforms, with a strong focus on AI workloads Proven hands-on experience developing analytical and event-driven simulation models for system-level performance evaluation. Deep understanding of AI system hardware architectures , including compute, memory hierarchies, and high-performance interconnects. Strong knowledge of modern and emerging AI workloads, including LLMs, DLRMs , and large-scale training and inference systems. Demonstrated ability to translate workload characteristics and modeling results into actionable architectural design decisions . Proficiency in Python, C++, and PyTorch for modeling, analysis, and experimentation. Excellent written, verbal, and presentation communication skills, with the ability to influence technical direction across tea…