Technical Program Manager II, ML Model Evaluation, Google Workspace

Google

Education
Benefits
Skills

The application window will be open until at least June 24, 2025. This opportunity will remain online based on business needs which may be before or after the specified date.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Boulder, CO, USA; Seattle, WA, USA; Sunnyvale, CA, USA.

Minimum qualifications:

  • Bachelor's degree in a technical field, or equivalent practical experience.
  • 2 years of experience in program management.
  • Experience with human evaluation or automated evaluation frameworks for Artificial Intelligence and Machine Learning models (i.e. quality evaluation, quality hill climbing, iterative model improvements, etc.)

Preferred qualifications:

  • 2 years of experience managing cross-functional or cross-team projects.
  • Experience managing day-to-day execution of AI programs, launching successful app products in the market, and developing products with an understanding of current AI technologies and services.
  • Experience working directly with Enterprise customers.
  • Experience launching features to consumers through frontend software development or backend platform development.
  • Experience with PLX Dashboarding, scripting, or Apps Script.

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 play a pivotal role in shaping the user experience, working across a range of components in the stack, including Frontend, Serving, Integrations, and more. Your primary focus will be to improve our data, quality, and evals across Workspace teams, partnering closely with AI Platform Engineering and Product Management to drive improvements across all Workspace applications. You'll collaborate with teams across Google, including DeepMind and Gemini.

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.

The US base salary range for this full-time position is $132,000-$189,000 + 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.

Responsibilities

  • Partner closely with product management, engineering, and User Experience (UX) leads to understand and shape eval quality strategy, data coverage, and the coupling of auto evaluations with human evaluations.
  • Understand the complexities of building AI powered features for new and scaled products.
  • Work closely with central teams on machine learning model evaluation spending, partnering with teams across Google Workspace and finance.
  • Identify risks and corresponding mitigation plans, implementing those solutions accordingly.
  • Manage multiple, time-sensitive projects simultaneously.
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Confirmed 22 hours ago. Posted 2 days ago.

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