Join Google's innovative AI and Infrastructure (AI2) organization as a PhD Software Engineer, focusing on Fleet Analytics. You'll leverage specialized research expertise to tackle complex, real-world challenges at an unprecedented scale. This role is pivotal in designing and managing the software, hardware, and ML systems infrastructure that powers essential Google services and Cloud products.

As part of a dynamic team, you will contribute to redefining possibilities by delivering AI and Infrastructure at unparalleled scale, efficiency, and reliability. Your work will empower Google customers, including internal teams, Google Cloud clients, and billions of users worldwide. Be a driving force behind groundbreaking innovations, from cutting-edge AI models to the essential platforms enabling future development.

Key responsibilities include designing, developing, and maintaining advanced optimization models, such as mixed integer programming. You will also be responsible for developing other critical platform capabilities and experimenting with foundational tech stacks for comparison and selection.

Implementation, deployment, and rollout of features will follow safe practices. Effective interaction with users and partner teams is essential for feature scoping, rollout support, and training. You will also contribute to the design and development of other platform capabilities.

To excel in this role, a PhD degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience, is required. Demonstrated experience in applying mathematical techniques to solve large-scale, intractable problems is essential.

Candidates should possess experience conducting advanced research in Computer Science, Applied Mathematics, or relevant fields. Preferred qualifications include a PhD in Statistics, Applied Mathematics, or Operations Research, along with experience in mathematical optimization techniques and an understanding of cloud design considerations and limitations.