EDA/CAD Custom Tool Development Engineer, Google Cloud

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in ASIC Chip Design.
  
• 5 years of experience with hardware electronic design automation tools.
  
• Experience in Python/C++ programming.
  
• Experience in writing code and design practices.
  

Preferred qualifications:

• Experience planning and deploying new tools and flows to users.
  
• Experience in AI/ML methods for ASIC development.
  
• Knowledge of chip design processes such as verification, design, and implementation.
  
• Ability to present and explain novel methods to users.
  
• Excellent programming skills (e.g., C, C++ or Python).

About the job

In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.

In this role, you will help deliver products that have an impact on the technical infrastructure. You will provide leadership in a fluid environment with a focus on infrastructure for chip design. You will also lead complex technical projects from the concept/planning stage through execution and closure. You will enable the wider team to deliver designs of different application areas, including ML/AI acceleration by developing tools relying on AI/ML techniques. You will lead chip design process improvement projects.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Responsibilities

• Partner with the Google Deepmind team to incorporate AI/ML techniques in chip design methodology and integrate into development flow.
  
• Partner with Chip Project teams to influence and standardize methodology across projects and functional areas (e.g., Design, Verification, Emulation, and other front end domain).
  
• Propose, design, and implement software automation addressing bottlenecks in today's ASIC and SoC EDA flow. Perform or guide technical evaluations of tools and their AI capabilities, and drive planning for possible deployment. 
  
• Lead the development of internal software tools and automation efforts, participate in design reviews, and engage in influencing and scheduling trade-off discussions. Collaborate to identify and create opportunities for improved chip design across Google.
• Work directly with a hardware team on projects-prototype and deploy tools to make a positive impact on Google's chip hardware development process.