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Product Manager, Large Model Infrastructure Efficiency and Scaling
Product Manager, Large Model Infrastructure Efficiency and Scaling-March 2024
San Francisco
Mar 21, 2025
ABOUT GOOGLE
Our mission is to organize the world’s information and make it universally accessible and useful.
10,000+ employees
Technology
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About Product Manager, Large Model Infrastructure Efficiency and Scaling

  Minimum qualifications:

  Bachelor's degree or equivalent practical experience.

  10 years of experience in product management, consulting, co-founder or related technical role.

  5 years of experience building and shipping technical products.

  Experience developing or launching products/technologies within one or more of the following: cloud, SaaS, enterprise, internal tools, or supply chain networks.

  Preferred qualifications: Experience in one or more of the following: cloud infrastructure, SaaS, big data, security and privacy, development and operations, or artificial intelligence/machine learning.

  Experience training, fine tuning, and deploying large language models.

  Experience driving product roadmap, go-to-market strategy, and design discussions.

  Experience managing day-to-day technical and design direction.

  Knowledge of multiple functional areas (e.g., Product Management, Engineering, UX/UI, Sales, Customer Support, Finance, or Marketing).

  Ability to influence multiple stakeholders without direct authority.

  About the job

  At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.

  In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.

  One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.

  In this role, you will work on Google's large model infrastructure and with a focus on efficiency and scaling.

  Google Cloud accelerates organizations' ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology - all on the cleanest cloud in the industry. 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 $208,000-$306,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. 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

  Develop a strategic vision for Google's large model infrastructure and with a focus on efficiency and scaling.

  Identify opportunities to improve the efficiency of the team's training, serving, and fine tuning workloads.

  Drive coherence between Hardware and Software development programs to enable most productive use of the systems as deployed.

  Develop effective partnerships with Google's product areas and understand their evolving needs for large scale Generative AI training and serving. Help understand and improve developer experiences, and thereby enable more productive use of Google's Machine Learning (ML) resources.

  Own and set the strategy, roadmap, and implementation for multiple areas of focus, balancing short- and long-term priorities against various business needs.

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