Senior Software Engineer, ML Infrastructure, Cloud AI

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in C++.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience developing large-scale infrastructure, distributed systems or networks, or with compute technologies, storage or hardware architecture.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 1 year of experience in a technical leadership role.
• Experience in compilers or runtimes.
• Knowledge of sustainability projects (code health, simplification etc.).
• Understanding of sustainability projects (code health, etc.) while working mid-stack/doing more end-to-end work.

The XLA (Accelerated Linear Algebra) compiler is used across the Research to Production pipeline for both Training and Serving use cases for TPU, GPU and CPU accelerators. In this role, you will work on projects that improve generalization across different hardware, frameworks and use cases by simplifying and standardizing compiler integration across different stacks.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

The US base salary range for this full-time position is $166,000-$244,000 + 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.

• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Understand how accelerator compiler and runtimes interact at a high level.
• Close infra gaps to help with end-to-end ML stack maturation (e.g., reduce number of ways something is done, improve reproducibility, improve tooling, improve usability).
• Develop and apply metrics to understand the problem you are solving and gage status/success as needed.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.