Software Engineering Manager, Workload Benchmarking, Google Cloud Platform Compute

Google

  • Kirkland, WA
  • Permanent
  • Full-time
  • 2 days ago
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Sunnyvale, CA, USA.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 with compute technologies, storage or hardware architecture.
  • 3 years of experience in a technical leadership role overseeing projects.
  • 2 years of experience in a people management, supervision/team leadership role.
Preferred qualifications:
  • Master's degree or PhD in Computer Science or related technical field.
  • 3 years of experience working in a structured organization.
  • Experience developing accessible technologies.
  • Experience with internal quality and repro testing to cover critical user journeys (CUJs).
  • Ability to collaborate with internal infrastructure teams to identify bottlenecks and expand capacity as needed.
  • Ability to drive continuous product improvement through bug fixes and short-term feature enhancements.
About the jobLike 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 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 .Responsibilities
  • Manage a team of 6-8 engineers, supporting the new model benchmarking needs for customers. Identify and resolve technical bottlenecks to drive customer success.
  • Understand the state of art models and contribute to the tooling for TPU/GPU Inference/training. Partner with customers to optimize AI/ML model performance on Google Cloud infrastructure.
  • Collaborate with internal infrastructure teams to enhance support for demanding AI workloads. Develop and deliver high-quality training materials and demos for customers and internal teams.
  • Conduct design and code reviews to ensure adherence to best practices across technologies. Maintain and update documentation and educational content based on product changes and user feedback.
  • Triage, debug, and resolve system issues by analyzing root causes and operational impact. Design and implement specialized machine learning (ML) solutions, effectively leveraging advanced ML infrastructure.
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 and If you have a disability or special need that requires accommodation, please let us know by completing our .

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