Senior Manager, GPU Machine Learning Production

Minimum qualifications:

• Bachelor’s degree, or equivalent practical experience.
  
• 8 years of experience programming in C++, Java, Python, Kotlin or Go.
• 5 years of experience in a technical leadership role.
• 5 years of experience in a people management or team leadership role.
• 5 years of experience with embedded systems.
• 5 years of experience with software architecture.

Preferred qualifications:

• Experience in steering hardware platforms through the NPI phase, stabilizing them, and successfully transitioning them into GA.
• Experience in organizational design, consolidating fragmented, project-funded task forces into a centralized and sustainably funded operational engineering team.
• Experience designing or integrating automated diagnostic frameworks and health management systems to rapidly root-cause hardware and software faults across a fleet.
• Experience bridging hardware, systems software, and site reliability teams to advocate for "design for supportability" in future hardware iterations.
• Experience operating within a cloud or enterprise environment, partnering directly with customers to translate their operational pain points into upstream infrastructure improvements.

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.

The GPU Platform Software team is responsible for building a bleeding edge platform that will power Google services and world's ML. GPU compute platforms enables Google services like Search, Ads, Google Cloud, Deep Mind, etc. The team develops the system software, firmware, tools, and tests to bring GPUs to Google's compute infrastructure.

In this role, you will be at the forefront of scaling our most critical Artificial Intelligence (AI) infrastructure. Our rapidly expanding GPU fleet presents unique, high-impact organizational issues, transforming distributed, New Product Introduction (NPI)-focused task forces into a centralized, cohesive, and standing MLPS organization.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.
The US base salary range for this full-time position is $262,000-$365,000 + 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.In this role, you will be at the forefront of scaling our most critical Artificial Intelligence (AI) infrastructure. Our rapidly expanding GPU fleet presents unique, high-impact organizational issues, transforming distributed, New Product Introduction (NPI)-focused task forces into a centralized, cohesive, and standing MLPS organization.
The US base salary range for this full-time position is $262,000-$365,000 + 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 salar