Software Engineer, Persistent Disk, PhD, Early Career, 2026

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. 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’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. 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.

As a key member of a small and versatile team, you design, test, deploy and maintain software solutions.

Within Google Cloud, the AI and Infrastructure (AI2) organization is at the forefront of creating AI/ML capabilities. We are responsible for designing and managing the software, hardware, and Machine Learning (ML) systems infrastructure that power essential Google services such as Search and YouTube, as well as Google Cloud products.

As a PhD Software Engineer within AI2, your specialized research expertise will be instrumental in solving complex, real-world problems on an unprecedented scale. You'll engage in innovative projects spanning areas like AI/ML, networking, data storage, security, and distributed systems.

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.

Responsibilities

• Drive research initiatives to explore next-generation storage architectures, prototype novel backup/replication algorithms, and evaluate emerging technologies.
• Improve the reliability, scale, and performance of backup and replication solutions while maintaining healthy release cycles.
• Work closely with partners and internal stakeholders to translate complex engineering and research efforts into enhanced customer satisfaction and tangible business growth.

Qualifications

Minimum qualifications:

• PhD degree in Computer Science, Electrical Engineering, or a related technical field.
• Experience with research and development of data storage, backup, or disaster recovery technologies.
• Experience conducting research on storage systems, including publishing findings.
• Experience in architecture or development of distributed systems, including concurrency, multi-threading, or synchronization.
• Experience coding in one of the following programming languages including but not limited to: C, C++, Python Java or Golang.

Preferred qualifications:

• Experience with data management tools and technologies including data pipelines frameworks, database engines, and file and object stores.
• Experience contributing to research communities including publishing at conferences (e.g., CVPR, NeurIPS, ICCV/ECCV, BMVC).
• Expertise in designing and implementing complex systems for either production or experimental use.
• Proficiency in performance analysis or the analysis of systems data.
• Excellent engineering capabilities.

• Availability to commence a full-time position in 2026.