Silicon Networking Microarchitecture and RTL Lead

1 Day ago • 8 Years + • Research & Development

Job Summary

Job Description

This role involves leading the microarchitecture and RTL design of complex IPs and subsystems for networking within Google Cloud's TPU (Tensor Processing Unit) technology. Responsibilities include owning the microarchitecture and implementation of these components, collaborating with architecture, firmware, and software teams, driving design methodology and improvements, and leading power, performance, and area optimizations. The ideal candidate will have extensive experience in ASIC development using Verilog/SystemVerilog, VHDL, and a strong understanding of networking concepts like packet processing and congestion control. This position requires working closely with other teams to deliver high-quality designs for next-generation data center accelerators. The work contributes directly to Google's AI/ML infrastructure and impacts millions of users.
Must have:
  • 8+ years ASIC development experience
  • Verilog/SystemVerilog, VHDL expertise
  • Experience in ASIC design verification, synthesis, timing/power analysis, and DFT
  • Micro-architecture and design of networking IPs/Subsystems
  • Collaboration with Architecture, Firmware, and Software teams
Good to have:
  • Scripting languages (Python or Perl)
  • SoC designs and integration flows
  • Knowledge of bus architectures, fabrics/NoC, processor design, accelerators, or memory hierarchies
  • High-performance and low power design techniques

Job Details

Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 8 years of experience in ASIC development with Verilog/SystemVerilog, VHDL.
  • Experience in ASIC design verification, synthesis, timing/power analysis, and Design for Testing (DFT).
  • Experience in micro-architecture and design of IPs and Subsystems in Networking domain such as Packet processing, bandwidth management, congestion control, etc.

Preferred qualifications:

  • Experience with scripting languages (e.g., Python or Perl).
  • Experience in SoC designs and integration flows.
  • Knowledge of bus architectures, fabrics/NoC, processor design, accelerators, or memory hierarchies.
  • Knowledge of high-performance and low power design techniques.

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 be part of a team developing cutting-edge ASICs used to accelerate and improve traffic efficiency in data centers. You will collaborate with members of architecture, verification, power and performance, physical design to deliver high quality designs for next generation data center accelerators. You will solve technical problems with innovative micro-architecture and practical logic solutions, and evaluate design options with complexity, performance, power and area in mind.

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

  • Own microarchitecture and implementation of complex IPs and subsystems in the Networking domain.
  • Work with Architecture, Firmware, and Software teams to drive feature closure and develop micro-architecture specifications. 
  • Drive design methodology, libraries, debug, code review in coordination with other IPs Design Verification (DV) teams and physical design teams.
  • Identify and lead power, performance, and area improvements for the domains owned.

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