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Home›Jobs›Google›Senior Technical Program Manager I, Machine Learning, Google Cloud Platforms
Google

About Google

Empowering the world through technology and information

🏢 Tech👥 100K+📅 Founded 1998📍 Mountain View, California, United States

Key Highlights

  • Over 100,000 employees globally
  • Headquartered in Mountain View, California
  • Parent company Alphabet Inc. valued at $1.5 trillion
  • Google Cloud Platform serves millions of customers

Google LLC, headquartered in Mountain View, California, is a global leader in internet-related services and products, including its flagship search engine, Google Search, and the Android operating system. With over 100,000 employees, Google also offers cloud computing services through Google Cloud P...

🎁 Benefits

Google offers competitive salaries, equity options, generous PTO policies, comprehensive health benefits, and a remote work policy that allows flexibi...

🌟 Culture

Google is known for its engineering-first culture, emphasizing innovation and collaboration. The company fosters a unique environment that encourages ...

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Google

Senior Technical Program Manager I, Machine Learning, Google Cloud Platforms

Google • Sunnyvale, CA, USA

Posted 1 month ago🏛️ On-SiteSeniorTechnical program manager📍 Sunnyvale
Apply Now →

Skills & Technologies

Machine learningProgram management

Job Description

Minimum qualifications:

  • Bachelor's degree in a relevant field, or equivalent practical experience.
  • 8 years of experience in program management.
  • 8 years of machine learning work experience.

Preferred qualifications:

  • 8 years of experience managing cross-functional or cross-team projects.

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.

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.

The US base salary range for this full-time position is $183,000-$271,000 + 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 about benefits at Google.

  • Implement communications standards across a portfolio of programs including executive and key partner communications.  
  • Establish a reliable and visible cadence for program reviews, decision-making, prioritization, and Resource Stewardship (effective deployment of machine and people resources) whereby improvements such as efficiency and utilization gains are measurable and the impact can be felt organization wide. 
  • Lead a governance structure that drives effective executive decision-making. Ensure governance structure effectively exposes and mitigates dependencies.  
  • Seek out and identify change management opportunities that increase program velocity and which affect multiple teams. 
  • Define/manage a program portfolio solving problems that target high business impact for the organization and product area.

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