Staff Software Engineer, Emerging On-Prem AI Infrastructure

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience programming in C++.
• 5 years of experience testing, and launching software products.
  
• 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
  
• 3 years of experience with software design and architecture.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• Experience with or passion for building deep system skills.
• Experience with large-scale fleet operations.
• Understanding of low level system software, OS, firmware, low level networking, or hardware.

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 is looking to build the next generation of on prem AI infrastructure to bring the best of Google to empower Frontier model and AI solution builders to advance the AI around the world. We're looking for engineers with exposure to fully integrated AI infrastructure systems, from hardware to software design and workload management, to developing large-scale training and inference workloads, and optimizing performance

In this role, you will be building the AI infrastructure for the future, so if you are interested in building a brand new product in a changing environment, rather than just evolving an existing one, this may be the role you are looking for.

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 project success by setting the technical goal and roadmap.
• Mentor software engineers on the team will be a top priority of this role.
• Deliver features in a changing environment working with other product areas/teams in Google. Scoping bold ambiguous problems into tractable projects and delivering results incrementally is a key responsibility.
• Design and lead development of test infrastructure. Ensure central responsibility is taken for diagnostics and troubleshooting of end-to-end supportability issues, to uncover and address complex technical problems, and the building of solutions including tools and repair automation systems.
• Implement and drive continuous improvement via success metrics for the team, spanning release quality metrics and customers facing operations.