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.

Google Kubernetes Engine (GKE) is a managed, production-ready environment for deploying containerized workloads and services. The team engineers GKE as the stable and reliable platform for customers running the Artificial Intelligence/Machine Learning (AI/ML) workloads. We enable the training of the Generative AI (GenAI) models by establishing GKE as the recognized leader for production-ready environments while advancing the core Kubernetes ecosystem. We work with customers to understand and solve their AI/ML scalability and reliability needs on GKE.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

Responsibilities

• Drive technical success for customers by providing expert engineering guidance, troubleshooting, and custom-engineered solutions to overcome scalability and reliability tests.
• Address the problems of unprecedented scale, improve system reliability, and impact other teams' performance.
• Utilize expertise to engage and enhance the Software Development Lifecycle (SDLC) (e.g., design, development, testing, deployment, maintenance, and improvement).
• Collaborate within and across teams and learn. Work on cloud technologies designed for performance and reliability.
• Contribute to Google-internal and Open Source (OSS) projects.