Software Engineer, Developer Tools, Silicon

1 Month ago • 2-4 Years • Research & Development

Job Summary

Job Description

As a Software Engineer in Developer Tools for Silicon at Google, you will design, develop, test, deploy, maintain, and enhance software solutions for diagnosing and analyzing system issues in Google's custom silicon. Responsibilities include developing software tools and scripts, creating a dongle-less debugger via USB or other interfaces, presenting analytics via CLI and GUI, applying machine learning to pinpoint root causes and self-recovery methods, and collaborating with cross-functional teams to build APIs and user interfaces. You'll also enable test automation and participate in hardware/software co-design efforts. This role requires expertise in Python and C/C++, experience with on-chip debugging/tracing/profiling, and a strong understanding of software development principles.
Must have:
  • 2+ years software development (Python or C/C++)
  • On-chip debugging/tracing/profiling experience
  • Develop software tools & scripts for system diagnosis
  • Create dongle-less debugger via USB or existing interface
  • Present analytics in CLI and GUI
Good to have:
  • Master's/PhD in CS or related field
  • Experience with ARM CoreSight architecture
  • Experience with commercial JTAG debug solutions
  • Experience with Perfetto or equivalent profiling tools
  • Machine learning application for root cause analysis

Job Details


Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in Python or C/C++.
  • Experience with on-chip debugging/tracing/profiling solutions, or 1 year of experience developing firmware or embedded operating systems.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 2 years of experience in Python scripting and C/C++ development for firmware applications.
  • Experience developing tools on ARM CoreSight architecture, commercial JTAG debug solutions, or other debugging methodology on the HW/SW boundary.
  • Experienced in Perfetto or equivalent profiling tools.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, with your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

Responsibilities

  • Develop software tools and scripts to diagnose, analyze system issues of Google custom silicon. Develop a dongle-less debugger via USB or any existing peripheral interface. 
  • Present the analytics in both CLI (Command Line Interface), and GUI (Graphical Interface). 
  • Apply machine learning on the analytics to pinpoint the likely root causes and the corresponding self-recovery methods.
  • Engage cross-functional with Google teams to build APIs, tools, and user interfaces. Enable test automation to collect the analytics automatically in development test farms.
  • Review hardware designs, prototype software-based hardware mocks, and engage in hardware/software (HW/SW) co-design efforts to get the full understanding of the debug or performance features implemented in the tools.

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