ASIC Methodology, Flow and Integration Engineer
NVIDIAJob Title
ASIC Methodology, Flow and Integration Engineer
Role Summary
Responsible for design methodology, automation, and integration for NVIDIA's High Speed IO team. Own the integration process across NVIDIA SoC and GPU projects and collaborate with global RTL, verification, physical design, and architecture teams.
Focus areas include building reusable infrastructure, improving scalability and turnaround time, and driving full-chip debug and connectivity across multiple hierarchies and technology nodes.
Experience Level
Entry-level; recommended 2+ years of relevant ASIC design integration and methodology experience.
Responsibilities
Primary responsibilities include integration, methodology development, automation, and cross-team collaboration:
- Own full-chip and block-level integration across multiple SoC and GPU projects.
- Stitch RTL units, manage hierarchy, and ensure seamless connectivity.
- Define and evolve internal design methodologies to improve scalability, quality, and turnaround time.
- Build automation pipelines using Python or Perl to streamline integration, debug, and delivery.
- Develop modular, reusable systems deployable across different SoC/GPU architectures.
- Collaborate with RTL, verification, physical design, and architecture teams to ensure flow compatibility and design readiness.
- Drive full-chip debug efforts and resolve connectivity and functional issues across hierarchies and technology nodes.
- Contribute to continuous improvement of internal standards and mentor engineers on flow usage and integration practices.
Requirements
Key skills and experience required (must-have) and preferred (nice-to-have):
Must-have
- Experience in design integration and methodology for ASIC design, including RTL integration and hierarchy management.
- Comprehensive understanding of IP development flows and build flows.
- Practical experience building automation using Python or Perl.
- Strong debugging, analytical, and problem-solving skills for complex full-chip issues.
- Effective interpersonal and influencing skills for collaboration with distributed, matrixed teams.
Nice-to-have
- Exposure to AI tools such as Claude or Cursor.
- Experience across multiple technology nodes and large SoC/GPU projects.
Education Requirements
Bachelor's (BS/B.Tech) or Master's (MS/M.Tech) in Electrical Engineering, Electronics & Communication, Computer Science, or a related technical field; or equivalent practical experience. The role mentions 2+ years of relevant industry experience.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
