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)

 What You’ll Do
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 Senior Staff AI System Architect who will play a key 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

• 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 AI workloads (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.
• Lead the architecture team with strong technical direction, shaping system‑architecture strategy and advancing key innovations
• 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, 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 teams.
• A collaborative mindset, intellectual curiosity, and resilience in tackling complex, open-ended system-level challenges. 
• You’re inclusive, adapting your style to the situation and diverse global norms of our people. 
• You approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborative, building