Senior Asic Design Methodology Engineer

NVIDIA NVIDIA · Semiconductors · Shanghai, China

Senior ASIC Design Methodology Engineer at NVIDIA, focusing on building the automation backbone for GPU memory subsystems. The role involves IP modularization, designing scalable flows, and applying AI-driven automation to improve efficiency and reliability. Key responsibilities include defining metrics, developing tools, and applying AI techniques for issue diagnosis and workflow enhancement. Requires a Master's degree or equivalent experience in Electrical/Computer Engineering, strong scripting skills, and understanding of ASIC/SoC concepts. Experience with AI agents for engineering workflows is a plus.

What you'd actually do

  1. Lead the modularization of the GPU Memory Subsystem into clear, well‑defined compartments/units, ensuring robust and well‑specified interfaces between modules.
  2. Work with front‑end IP, integration, design, and verification teams on infrastructure, build, and flow topics, proactively resolving flow‑related issues across the design.
  3. Define and track metrics/KPIs to understand build dependencies between units/compartments and use these insights to drive flow and infrastructure improvements.
  4. Design, develop, and maintain tools and automation flows that reduce manual effort, improve team productivity, and support more complex GPU designs.
  5. Apply AI techniques (e.g. agents, prompt engineering, workflow orchestration) to diagnose issues, analyze logs, and enhance workflows.

Skills

Required

  • Master’s degree or 2+ years equivalent experience in Electrical/Computer Engineering or a related field
  • Solid experience with build/flow automation
  • Strong skills in industry-standard scripting languages (e.g. Python, Perl, Makefile, or similar)
  • Good understanding of ASIC/SoC concepts and front‑end design or verification flows, with a focus on automation, methodology, and efficiency
  • Proven experience in process automation or efficiency improvement, including identifying bottlenecks and proposing practical, data‑driven solutions
  • Good communication skills
  • Strong spoken English
  • Ability to collaborate effectively across teams

Nice to have

  • Experience building or using AI agents for engineering workflows, including prompt engineering and workflow orchestration
  • Familiarity with dependency management or foundational concepts in large hardware development projects

What the JD emphasized

  • AI-driven automation
  • AI techniques (e.g. agents, prompt engineering, workflow orchestration)