Technical Program Manager II, Demand Planning, Cloud Supply Chain
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Minimum qualifications:
- Bachelor's degree in a technical field, or equivalent practical experience.
- 2 years of experience in program management.
- Experience in Supply Chain Planning in the Cloud or Machine Learning industry.
- Experience in Scenario Modeling or Demand Planning.
Preferred qualifications:
- 2 years of experience in managing cross-functional or cross-team projects.
- Experience with Resource Management at a tech company.
- Experience in working with executive stakeholders and managing engaging opinions and viewpoints.
- Experience in collaborating with partners and customers to solve problems.
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.
In this role, you will transform Demand Planning of the ML Fleet at Google. You will work with Google operations and deployment teams, supply chain, data center infrastructure, networking, and software engineering teams to define and deliver the future state of optimal resource management within Google. You will include the location deployment planning, the balancing of resource distribution against supply chain, data center infrastructure, network, shared service, and budgetary constraints, and the implementation of tools and policies to optimize resource management across the entire engineering stack at Google.
Responsibilities
- Manage the intake, prioritization, approvals, allocation, and stakeholder management for capacity needed for critical ML launches.
- Scale systems by rebuilding or supporting the existing Google platform, to meet the needs of users.
- Collaborate and support Machine Learning programs at Google.
- Identify opportunities to scale Machine Learning Fleet operations and lead process improvement initiatives.
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