Join Google's pioneering team and contribute to the future of technology, shaping how billions interact with information. We are seeking innovative engineers to develop next-generation AI/ML capabilities within Google Cloud's AI and Infrastructure organization (AI2). This role is crucial for powering essential Google services and Google Cloud products, offering the chance to work on large-scale, complex problems.

As a PhD Software Engineer, you will leverage your specialized research expertise in areas such as AI/ML, networking, data storage, security, and distributed systems. You will have opportunities to switch teams and projects, growing with our fast-paced business. We value versatility, leadership, and enthusiasm for tackling new challenges across the full technology stack.

Google Cloud empowers organizations worldwide to digitally transform. We provide enterprise-grade solutions utilizing Google's advanced technology and tools for sustainable development. Our trusted partnership enables growth and helps customers solve their most critical business challenges across over 200 countries and territories.

Design, test, deploy, and maintain robust software solutions as a key member of a versatile team. Write high-quality product or system development code, adhering to best practices through collaborative design and code reviews.

Contribute to the enhancement of documentation and educational content, adapting it based on product updates and user feedback. Effectively triage and resolve product or system issues through in-depth analysis and debugging.

Implement advanced solutions within specialized ML domains, leverage ML infrastructure, and actively contribute to model optimization and data processing pipelines.

A PhD degree in Computer Science, Electrical Engineering, or a related technical field is required. Candidates must possess at least 1 year of experience in one or more of the following areas: Speech/audio technology, reinforcement learning, ML infrastructure, or another specialized ML field.

Proficiency is needed in ML infrastructure, including model deployment, evaluation, optimization, data processing, and debugging. Experience coding in at least one of the following languages is essential: C, C++, Python, Java, or Golang.

Preferred qualifications include 2 years of experience with data structures and algorithms, and expertise in areas like AI, distributed systems, or machine learning. A demonstrated history of publishing in prestigious academic venues is highly valued. Availability to start a full-time position in 2026 is necessary.