Software Engineer, Open Source, AI/ML, Developer Infrastructure

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Kirkland, WA, USA; New York, NY, USA; San Francisco, CA, USA; Sunnyvale, CA, USA.Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in C++, or 1 year of experience with an advanced degree in an industry setting.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
  
  

Preferred qualifications:

• Experience with building, testing, and releasing software, and developing AI/ML models.
• Experience with open-source ecosystems like Python packaging, Cloud, and an object oriented programming language such as C++ or Python.
• Experience with building out scalable and secure CI/CD systems and OSS tooling, such as Kokoro and Copybara, as well as systems administration on Linux, MacOS, and Windows.
• Experience with developer infrastructure tooling such as Docker, Terraform, or GCP.
• Familiarity with C++ compilation, and build tools such as Bazel/Blaz, as well as compiler development.
  
  

About The Job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

Core Machine Learning (ML) works with a wide range of technologies such as Bazel, Git, Remote Build Execution, Kokoro, Copybara, and a large amount of custom tooling. Having a huge global user base makes the quality of software critically important. Excellence in releasing, contributing, and testing is crucial to the success of ML projects. JAX, TensorFlow, and XLA are used both at Google as well as by academic users and industry partners (such as NVIDIA and Intel).

You will have an opportunity to collaborate with engineers/leads across the ML ecosystem and make contributions that affect the quality-of-life for distinguished engineers in the company and beyond.

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.

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 .

Responsibilities

• Design and enhance dev, build, testing, and release infrastructure for internal/external development of the ML software stack.
• Accelerate ML development and experimentation through new, innovative tools.
• Build infrastructure for releasing the ML software stack that maximizes open-source reliability and adoption.
• Identify common patterns of software failures and develop innovative preventative solutions. Maintain and optimize the multi-platform CI test suite.
• Update ML dependencies to the latest community standards (e.g., Python, C++, CUDA, Manylinux). Promote best development practices across teams and the OSS community.
  
  
  

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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.