Software Engineer, Platforms and Devices, Chrome

Google•Seattle, WA

About The Position

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. With 4.2B+ users, Chrome drives the web and browser ecosystem forward by showcasing a steady stream of new features and platform capabilities. Chrome browser's strategy is to become more purpose built, to be smarter, personalized, and proactive. That's where our team comes in. The Chrome Intelligence team’s goal is to build both generative Artificial Intelligence (AI) and non-generative AI Machine Learning features and capabilities to deliver on Chrome’s strategy. The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Requirements

Bachelor’s degree or equivalent practical experience.
5 years of experience programming in C++, Java, Python or Kotlin.
1 year of experience with Machine Learning infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Nice To Haves

Master's degree or PhD in Computer Science or related technical field.
2 years of experience with performance, large scale systems data analysis, visualization tools, or debugging.
2 years of experience with data structures or algorithms in either an academic or industry setting.
Experience developing accessible technologies.
Experience in code and system health, diagnosis and resolution, and software test engineering.