ASIC Physical Design Tools, Flows, Methodologies Manager
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 manage and lead a team of TFM engineers responsible for the physical design flows that power our Tensor Processing Unit (TPU) products. You will guide your team in developing, deploying, and supporting a register-transfer level (RTL)-to-GDS infrastructure. You will bridge design engineering and electronic design automation (EDA) capabilities, balancing resources and managing priorities across projects, feature requests, and bug resolutions to ensure silicon delivery.
Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
- 10 years of experience with the register-transfer level (RTL)-to-GDS process and industry-standard electronic design automation (EDA) tools, including Synopsys, Cadence, and Siemens suites.
- 6 years of experience in a people management role, managing a team of engineers within an application-specific integrated circuit (ASIC) design, semiconductor, or EDA environment.
Preferred qualifications:
- Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
- Experience supporting tools, flows, and methodologies (TFM) for ASICs (e.g., artificial intelligence (AI) or machine learning (ML) accelerators) on process nodes.
- Proficiency with scripting and automation languages commonly used in EDA workflows, such as Python, Tcl, Perl, and Make.