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.
Design, develop, and maintain advanced optimization models (e.g., mixed integer programming).
Design and develop other platform capabilities.
Experiment and prototype for foundational tech stacks comparison and selection.
Implement, deploy, and rollout features following safe rollout practices.
Interact with users, partner teams for feature scoping, rollout support, and training.
Minimum qualifications
PhD degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.
Experience applying mathematical techniques to solve large-scale, intractable problems.
Experience conducting advanced research in Computer Science, Applied Mathematics, or relevant experience.
Preferred qualifications
PhD in Statistics, Applied Mathematics, Operation Research, or a related field.
Experience with mathematical optimization (e.g., LP, IP, MIP, NLP).
Understanding of private and public cloud design considerations and limitations in the areas of virtualization and global infrastructure, distributed systems, load balancing and networking.
PhD degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.
Experience applying mathematical techniques to solve large-scale, intractable problems.
Experience conducting advanced research in Computer Science, Applied Mathematics, or relevant experience.
