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

1 Month ago • 8-8 Years • Artificial Intelligence • $183,000 PA - $271,000 PA

Job Summary

Job Description

As a Senior Technical Program Manager at Google, you'll lead complex, multi-disciplinary projects related to Machine Learning on Google Cloud Platforms (GCP). Responsibilities include implementing communication standards across programs, establishing program review cadences, leading governance structures for effective decision-making, identifying change management opportunities, and defining/managing a program portfolio targeting high business impact. You will work with stakeholders to plan requirements, identify risks, manage schedules, and communicate with cross-functional partners. The role requires strong technical expertise and the ability to explain complex information to both technical and executive audiences. This position is crucial for the success of Google's machine learning initiatives and its impact on various Google services and Cloud offerings.
Must have:
  • 8+ years program management experience
  • 8+ years machine learning experience
  • Cross-functional project management
  • Executive communication
  • Resource stewardship
  • Problem-solving for high business impact
Good to have:
  • Experience managing cross-team projects
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


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.

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.

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 .

Responsibilities

  • 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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