Google

Google

Software Engineer, ML Systems and Cloud AI, Embedded and Networking, University Graduate, PhD, Campus, 2025

Apply Now
🌍Mountain View, CA, USA, Atlanta, GA, USA, Cambridge, MA, USA, New York, NY, USA, San Bruno, CA, USA, San Jose, CA, USA, Sunnyvale, CA, USA
3h ago
πŸ‘€ 34 views
πŸ“₯ 1 clicks

Job Description

Minimum qualifications:

  • PhD degree in Computer Science, or a related technical field, or equivalent practical experience.
  • Experience coding in C or C++.
  • Experience in embedded systems/firmware or networking

Preferred qualifications:

  • Experience with RPC protocols such as gRPC or Thrift. Experience with bus protocols: I2C/I3C, USB, PCIe, SPI, MCTP.
  • Experience with Network Architecture, Large-Scale Distributed Systems, IP Network, or Networking Protocols.
  • Knowledge of Unix/Linux environments, and kernel development.
  • Knowledge of one or more of the following: Microcontrollers, SoC, device drivers, hardware bringup, power management, ARM processors, performance optimization, file systems, bootloading, firmware, x86 assembly, system BIOS or hardware/software integration.
  • Ability to start full-time role in 2025.

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.

As part of the Machine Learning, Systems and Cloud AI, you have the opportunity to be a part of an organization that delivers AI/ML solutions and capabilities, developed and powered by Google Services, Frameworks and Infrastructure, supporting customers.

As a Software Engineer, your research expertise is invaluable to us. Apply your knowledge to real-world problems, that scale to billions of users. Explore a variety of projects, collaborate with teams, and contribute to products that are changing the world. Our engineering teams bring their deep knowledge and research experience to enhance our systems and products. Learn more about us here!

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

  • Lead and collaborate on team projects to carry out design, analysis, and development of advanced Machine Learning (ML) systems across the stack using your research expertise.
  • Study, diagnose, and resolve complex technical modeling and systems issues by analyzing the sources of the issues and the impact on quality.
  • Develop code and review code developed by other developers, and provide feedback to ensure best practices (e.g., style guidelines, accuracy, testability, and efficiency).
Apply Now

More Jobs at Google