Google is seeking a PhD Software Engineer to join its Fleet Analytics team. This role focuses on developing next-generation technologies that connect, explore, and inform billions of users worldwide. You will contribute to products handling massive-scale information, extending beyond web search. The position offers opportunities to work on critical projects, switch teams, and tackle diverse challenges across the full stack as the business evolves. Versatility, leadership, and enthusiasm for new problems are highly valued.

As an integral part of a dynamic, small team, you will be responsible for designing, testing, deploying, and maintaining innovative software solutions. Within the Google Cloud AI and Infrastructure (AI2) organization, you will be at the forefront of creating AI/ML capabilities. This includes managing the software, hardware, and ML systems infrastructure that powers essential Google services like Search and YouTube, as well as Google Cloud products. Your specialized research expertise will be crucial for solving complex, real-world problems at an unprecedented scale, engaging in projects related to AI/ML, networking, data storage, security, and distributed systems. The AI and Infrastructure team is dedicated to empowering Google customers with breakthrough capabilities, delivering AI and Infrastructure with unparalleled scale, efficiency, reliability, and velocity to Googlers, Google Cloud customers, and billions of users globally.

Key responsibilities include designing, developing, and maintaining advanced optimization models, such as mixed integer programming. You will also design and develop other essential platform capabilities.

Experimentation and prototyping will be crucial for selecting foundational tech stacks. Implementation, deployment, and rollout of features will follow safe rollout practices. Active interaction with users and partner teams is expected for feature scoping, rollout support, and training.

The minimum qualifications for this role include a PhD degree in Computer Science, Electrical Engineering, or a closely related technical field, or equivalent practical experience. Candidates should possess experience applying mathematical techniques to solve large-scale, intractable problems and have a background in conducting advanced research in Computer Science, Applied Mathematics, or a relevant domain.

Preferred qualifications include a PhD in Statistics, Applied Mathematics, or Operations Research, or a related field. Experience with mathematical optimization techniques such as LP, IP, MIP, and NLP is beneficial. A strong understanding of private and public cloud design considerations, including limitations in virtualization, global infrastructure, distributed systems, load balancing, and networking, is also highly desirable.