Silicon Networking RTL Design Engineer

1 Month ago • 8 Years + • Research & Development

Job Summary

Job Description

This role involves shaping the future of AI/ML hardware acceleration, specifically TPU technology for Google's demanding applications. You'll contribute to custom silicon solutions, leveraging design and verification expertise to verify complex digital designs focused on TPU architecture and integration within AI/ML systems. The role also includes developing cutting-edge ASICs to accelerate and improve data center traffic efficiency. You'll collaborate with various teams (architecture, verification, power/performance, physical design) to deliver high-quality designs for next-generation data center accelerators. Responsibilities encompass owning microarchitecture and implementation of complex IPs, working with other teams to drive feature closure, leading design methodology and improvements, and identifying power, performance, and area enhancements.
Must have:
  • Bachelor's degree in relevant field
  • 8+ years ASIC development experience (Verilog/SystemVerilog, VHDL)
  • ASIC design verification, synthesis, timing/power analysis, DFT experience
  • Micro-architecture and IP/subsystem design in networking (packet processing, bandwidth management, congestion control)
  • Own microarchitecture and implementation of complex IPs
Good to have:
  • Experience with scripting languages (Python or Perl)
  • SoC designs and integration flows
  • High-performance and low-power design techniques
  • Knowledge of bus architectures, fabrics/NoC, processor design, accelerators, or memory hierarchies

Job Details

Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • 8 years of experience in ASIC development with Verilog/SystemVerilog, VHDL.
  • Experience with 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 high performance and low power design techniques.
  • Knowledge of bus architectures, fabrics/NoC, processor design, accelerators, or memory hierarchies.

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 diverse 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.

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, etc. to specify and deliver high quality designs for next generation data center accelerators. You'll 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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