Staff Software Engineer, Emerging On-prem AI Infrastructure
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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:
- Experience building cloud or systems level infrastructure spanning the entire hardware and software stack.
- Experience in end-to-end diagnostics, troubleshooting, and supportability, with experience leading SWAT team efforts for complex issues and developing long term sustainable solutions.
- Familiarity with Service Level Objectives (SLOs)/metrics measurement, logs/telemetry/metrics integration with tools for enhanced operator experience.
- Understanding of low-level system software, OS, firmware, low level networking, or hardware, etc., with a passion for building system skills.
- Ability to work in a changing environment and navigate ambiguity, and a track record of delivering solutions for subtle or complex technical problems.
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.
In this role, you will have exposure to integrated AI infrastructure systems (GPU or TPU), from software to hardware design and workload management, to developing large scale training and inference workloads, and optimizing performance. You will be building large AI clusters using the latest technologies for AI acceleration and cluster interconnects and networking.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
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
- Drive project success by setting the technical goal and roadmap.
- Set priorities and projects for a team that delivers features in a fast-moving environment for both internal customers (other engineering teams) and external customers.
- 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 repair automation systems.
- Implement and govern the success metrics for the team, spanning Operational Plane metrics (e.g., Support case metrics, GSO case handling), and RMA/Spares metrics (e.g., swap and repair rate).
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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.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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.
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