Google-posted 3 months ago
$227,000 - $320,000/Yr
Full-time • Senior
Kirkland, WA
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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 be the key operational bridge between the ML engineering teams within technical infrastructure, product areas, and MLSA leadership. You will write a playbook across process, policy, and software while managing and influencing stakeholders spanning multiple organizations and different levels of responsibility. Your work will impact how Google allocates its AI resources. 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.

  • Lead complex, multi-disciplinary projects from start to finish.
  • Work with stakeholders to plan requirements and identify risks.
  • Manage project schedules and communicate with cross-functional partners.
  • Explain analyses and recommendations to executives.
  • Discuss technical tradeoffs in product development with engineers.
  • Act as the operational bridge between ML engineering teams and leadership.
  • Write a playbook across process, policy, and software.
  • Manage and influence stakeholders across multiple organizations.
  • Technical expertise in program management.
  • Experience leading complex projects.
  • Strong communication skills with cross-functional teams.
  • Ability to explain technical concepts to non-technical stakeholders.
  • Experience in machine learning and systems infrastructure.
  • Bonus
  • Equity
  • Comprehensive benefits package
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