Technical Program Manager III, GPU Infrastructure Reliability, Google Cloud
corporatefare_ Google place Seattle, WA, USA; Kirkland, WA, USA; +2 more; +1 more
Mid
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.
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XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Kirkland, WA, USA; Sunnyvale, CA, USA .
Minimum qualifications:
Bachelor's degree in a technical field, or equivalent practical experience.
5 years of experience in program management.
Experience with infrastructure reliability.
Experience with GPUs or GPU Systems.
Preferred qualifications:
5 years of experience managing cross-functional or cross-team projects.
5 years of experience in technical program management, with a focus on software engineering and ML infrastructure projects.
Knowledge of software development, distributed systems, and ML infrastructure or GPU systems.
Ability to think critically and solve problems.
Excellent project management skills, with experience with project planning, execution, and risk management.
Excellent communication and collaboration skills, with the ability to build relationships and influence across all levels of the organization.
About the job
A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.
As the Technical Program Manager, you will manage planning, execution, and delivery of projects related to ML workload monitoring and diagnostic tooling for AI HyperCompute Clusters. This tooling is essential to provide insights into performance degradation within ML workloads, enabling efficient identification and resolution of performance issues. You will also collaborate with cross-functional teams, including engineers, data scientists, and product managers to ensure successful project outcomes and drive the development of scalable solutions for ML performance monitoring and diagnostics.
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 $156,000-$229,000 + 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 aboutbenefits at Google (https://careers.google.com/benefits/) .
Responsibilities
Collaborate with cross-functional teams to define project scope, goals, and deliverables. Develop detailed project plans, identify dependencies, and manage timelines.
Communicate with stakeholders across engineering, product, and research to ensure alignment and drive progress.
Identify and mitigate risks that could impact project success as well as delivery. Drive projects to completion, ensuring high-quality results.
Understand the technical aspects of ML workload monitoring and diagnostics, including distributed systems, performance optimization, and ML model convergence.
Work with engineers, researchers, and product managers to translate business requirements into technical solutions.
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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 https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCPEEOPost.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.
