Software Engineering Manager, Emerging On-prem AI Infrastructure
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Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
Preferred qualifications:
- Experience in end-to-end (E2E) diagnostics, troubleshooting, and supportability combined with leading "SWAT team" efforts for issues and developing long term sustainable solutions.
- Experience building cloud or systems level infrastructure spanning the entire HW and SW stack or passion for building deep system skills.
- Understanding with deep systems and ability to guide a team in building sustainable systems.
- Familiarity with SLOs/metrics measurement, logs/telemetry/metrics integration with tools for enhanced operator experience.
- Ability to demonstrate comfort with changing priorities and ambiguity, and a track record of delivering solutions for subtle or technical problems.
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.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Google is looking to build the next generation of on-prem Artificial Intelligence (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/TLMs with exposure to fully integrated AI infrastructure systems Graphics Processing Unit or Tensor Processing Unit (GPU or TPU), from Hardware (HW) to Software (SW) design and workload management, to developing large-scale training and inference workloads, and optimizing performance with experience building large AI clusters using the latest technologies for AI acceleration and cluster interconnects and networking.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities
- Drive project success by setting the technical goals and roadmap for diagnostics/operational tooling and repair automation.
- Lead and manage the team, which includes a 40-60 split of Software Development Engineer (SDEs) and Software Engineers (SWEs) ensuring the right skill sets are in place for frontline support, debugging, and building sustainable systems.
- Ensure central responsibility is taken for diagnostics and troubleshooting of end-to-end supportability issues, to uncover and address technical problems, and the building of repair automation systems.
- Implement and govern the success metrics for the team, spanning Operational Plane metrics (e.g., Support case metrics, Global Services Operations (GSO) case handling), and Return Merchandise Authorization (RMA) or Spares metrics (e.g., swap and repair rate).
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