Engineering Manager, AI/ML Infrastructure

Seattle, WA, USA Advanced Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders;deep expertise in domain. Qualifications Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience in cloud computing emerging technologies or related technical fields. 3 years of experience in a technical leadership role. 3 years of experience with AI Platforms. 2 years of experience in a people management or team leadership role. Preferred qualifications: Master's degree or PhD in Computer Science or related technical field. 3 years of experience working in a complex, matrixed organization. About the job Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way. The Cloud GPU team is central to AI innovation, dedicated to building and maintaining an industry-leading GPU fleet and AI Platform. Our core mission is to empower Google Cloud's most sophisticated training and inference customers by providing unparalleled computational resources. We're responsible for the entire life-cycle of GPU offerings within Google Cloud, from the initial launch of new GPU families to ensuring their optimal reliability and operational excellence for cutting-edge AI workloads. Our team thrives at the intersection of hardware, software, data science, and applied AI and is constantly pushing the boundaries of what's possible in accelerated computing. 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. The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google . Responsibilities Manage a team of top AI/ML infrastructure engineers with an extremely strong roadmap and opportunity for further growth. Work on the foundational AI/ML infrastructure layer in Google Cloud by building new and supporting existing accelerator-based VM families and baremetal GPU instances. Lead the team responsible for managing and defending the health of GPU instances as we bring them up in our data centers and deliver them to customers. Lead the team to ruthlessly automate and improve the management and handling of GPU machines in our data centers -- with the goal to automate away any manual tasks through tools and services and the use of AI. Engage and work closely with core customers as they explore and onboard our infrastructure. Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. #J-18808-Ljbffr