Staff Engineer, AI System Architect; Hardware

Staff Engineer, AI System Architect (Hardware)

San Jose, California, United States

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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.

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 : 42854

• 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.
• 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 (