Senior Manager, GPU Machine Learning Production

SOFTWARE_ENGINEERING
USA
March 26, 2026
FULL_TIME

Job Overview

  • Date Posted
    March 26, 2026
  • Location
    USA
  • Expiration date
    --

Job Description

2026-03-17T14:31:39.725Z

114809886897775302

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.

Responsibilities

  • Guide the transition of GPU production support from fragmented, NPI-specific task forces into a centralized, standing organization.
  • Develop and execute a comprehensive, multi-year roadmap for GPU fleet stability, capacity turn-up, and automated health management, aligning with broader Cloud and AI infrastructure goals.
  • Anticipate the support needs for next-generation GPU architectures and proactively build the capabilities required for seamless NPI to General Availability (GA) transitions.
  • Sponsor and drive the development of advanced telemetry, debugging tooling, and automated remediation systems to scale fleet management and significantly reduce operational toil.
  • Serve as the executive escalation point for critical, systemic hardware and software issues on GPU Superpods.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Related Jobs