Google is seeking a Software Engineering Manager to lead their TPU Systems team within Platforms Infrastructure. This role is crucial in developing software for Google's custom-built AI computation chip (TPU), enabling large-scale AI hypercomputation in Google's data centers. The position involves managing a team that works on various aspects of the TPU software stack, from system software for individual TPU machines to superpod software connecting thousands of TPU chips.
The role requires a blend of technical expertise and leadership skills, with responsibilities spanning from technical project leadership to people management. You'll be working with cutting-edge AI technology that powers various Google services including Deepmind, Search, and Ads, as well as Cloud customers. The position involves all stages of TPU development, from design and system bringup to productionization of individual machines and large-scale AI hypercomputers.
As a Software Engineering Manager, you'll be responsible for setting team priorities, developing technical vision, and ensuring best practices in code development. The role requires significant experience in software development, particularly with C/C++, and a strong background in embedded systems. You'll be working at the intersection of hardware and software, requiring familiarity with networking protocols and machine learning concepts.
The position offers the opportunity to work on groundbreaking technology at one of the world's leading tech companies. You'll be part of Google Cloud, which serves customers in more than 200 countries and territories, helping organizations digitally transform their businesses. The role combines technical leadership with people management, making it ideal for someone who wants to impact both technology development and team growth.
This is a chance to be at the forefront of AI infrastructure development, working with state-of-the-art technology while leading and mentoring a team of talented engineers. The role requires a balance of technical depth, leadership skills, and strategic thinking, making it an exciting opportunity for experienced engineering leaders who want to shape the future of AI computing infrastructure.