Technical Program Manager, Machine Learning Strategy and Allocation
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Minimum qualifications:
- Bachelor's degree in a technical field, or equivalent practical experience.
- 8 years of experience in program management.
- Experience in Machine Learning Infrastructure.
Preferred qualifications:
- 8 years of experience managing cross-functional or cross-team projects.
- Ability to handle highly sensitive and confidential information with complete discretion.
- Ability to prepare presentations, develop and deliver executive level communications.
- Ability to navigate ambiguity, support multiple projects, and meet deadlines in a fluid environment.
- Ability to synthesize complex material for large and small audiences via executive communications, presentations, dashboards, and documentation.
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 a Technical Program Manager in the Machine Learning Strategy and Allocation (MLSA) team, you will drive a pivotal function at Alphabet responsible for optimizing the company's critical ML compute resources. This role sits at the intersection of AI strategy, finance, and product management, directly influencing Google's AI future. You will lead strategic, cross-functional programs to enhance ML capacity allocation in a highly dynamic and constrained environment. You will be curious, comfortable making data-informed recommendations, and able to own major programs while also supporting others in their ownership of similar initiatives. Success requires exceptional cross-functional leadership, executive-level communication, and a broad, adaptable technical understanding.
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.
Responsibilities
- Lead the development and execution of complex, multi-disciplinary programs to optimize ML compute allocation aligned with Google's AI strategy and company-level OKRs.
- Communicate complex allocation decisions and insights effectively to executive leadership (VP/SVP), fostering strong partnerships across Product Areas while navigating sensitive and confidential information.
- Drive strategic planning for ML capacity allocation, influencing resource decisions and continuously optimizing the portfolio to maximize Alphabet's return on ML investments.
- Establish and refine scalable program management processes for ML capacity planning, ensure consistent outcomes, data-driven decision-making, and robust governance over allocation recommendations. Identify opportunities to improve ML fleet utilization and reduce waste, implementing solutions that enhance the efficiency and predictability of ML resource management.
- Apply a broad technical understanding to evaluate complex ML infrastructure data, making impactful judgments and solving intricate allocation challenges that drive business value.
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