AI System Architect - NPU / GPU / Interconnect, ASICS Engineering

Company:

Job Area:

Engineering Group, Engineering Group > ASICS Engineering

General Summary:

We are seeking experienced architects with deep expertise in AI accelerators (NPU), GPUs, and/or high-performance system interconnects to define next-generation AI and data center compute platforms.

Successful candidates will possess strong architectural knowledge in one or more of the following areas:

• AI accelerator and NPU architecture
• GPU architecture, graphics, and compute systems
• High-performance system interconnects and data center fabrics

Key Responsibilities

Customer & Platform Architecture

• Engage with customers, partners, and internal stakeholders to understand AI workload requirements, deployment scenarios, performance targets, and system constraints.
• Translate customer and market requirements into scalable system architecture, technology roadmaps, and platform features.
• Drive architecture tradeoff analysis across performance, power, cost, scalability, and deployment requirements to influence product direction.

One or More of the Following Domains:

AI / NPU Architecture

• Analyze and optimize AI workloads including LLMs, Transformers, computer vision, multimodal AI, and recommendation systems.
• Drive HW/SW co-design across architecture, compiler, runtime, driver, and framework layers.
• Lead performance analysis and optimization across compute, memory, and communication subsystems.

GPU & Graphics Architecture

• Analyze graphics, rendering, compute, and AI workloads to optimize performance, efficiency, and scalability.
• Drive architecture of GPU compute pipelines, graphics pipelines, memory systems, scheduling, and data movement.
• Collaborate with graphics software, driver, runtime, and application teams to optimize workload execution and user experience.

System Interconnect & Data Center Architecture

• Architect high-performance data movement across compute, memory, storage, and networking subsystems.
• Define scale-up and scale-out architectures using PCIe, CXL, Ethernet, UALink, or similar communication fabrics.
• Drive architecture of cache-coherent fabrics, memory hierarchies, chiplet communication, and distributed AI systems.
• Lead system-level architecture decisions for scalability, performance-per-watt, latency, and overall system efficiency.

Required Qualifications

• BS/MS in Electrical Engineering, Computer Engineering, Computer Science, or related field.
• 10+ years of experience in AI accelerator, GPU, high-performance compute, system architecture, or related disciplines.
• Deep expertise in one or more of the following areas:
  • AI accelerator / NPU architecture
  • GPU architecture, graphics pipeline, and compute architecture
  • High-performance interconnects and communication fabrics
  • Data center system architecture
  • Memory hierarchy and bandwidth optimization
  • AI workload performance analysis and modeling
• Strong HW/SW co-design background with a solid understanding of how AI software stacks, compilers, runtimes, and drivers utilize underlying hardware resources.
• Demonstrated ability to drive architecture decisions across hardware, software, memory, and communication subsystems.

Language Requirements

• Fluent in both Mandarin Chinese and English.
• Able to lead technical discussions and collaborate effectively across global engineering teams.

Minimum Qualifications:

• Bachelor's degree in Science, Engineering, or related field and 8+ years of ASIC design, verification, validation, integration, or related work experience.
OR
Master's degree in Science, Engineering, or related field and 7+ years of ASIC design, verification, validation, integration, or related work experience.
OR
PhD in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.

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