Staff Software Engineer, AI Innovation and Research

Google is seeking a Staff Software Engineer for AI Innovation and Research. This role involves developing next-generation technologies that change how billions of users connect, explore, and interact with information. The ideal candidate will bring ideas from various areas, including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile.

The Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. They research, design, and develop new technologies and hardware to make user interactions with computing faster, seamless, and more powerful.

Key responsibilities include:

• Providing technical leadership on high-impact projects
• Facilitating alignment and clarity across teams on goals, outcomes, and timelines
• Managing project priorities, deadlines, and deliverables
• Designing, developing, testing, deploying, maintaining, and enhancing large-scale software solutions
• Triaging product or system issues and debugging/tracking/resolving by analyzing the sources of issues and their impact

The role requires a Bachelor's degree or equivalent practical experience, 8 years of experience in software development and with data structures/algorithms, 5 years of experience testing and launching software products, and 3 years of experience with software design and architecture. Experience with Machine Learning (ML) is also required.

Preferred qualifications include a Master's degree or PhD in Engineering, Computer Science, or a related technical field, 3 years of experience in a technical leadership role, and 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.

Google offers a competitive salary range of $189,000-$284,000 + bonus + equity + benefits, with individual pay determined by work location and additional factors such as job-related skills, experience, and relevant education or training.