Technical Program Manager III, AI/ML, Google Ads

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.

AdsML’s mission is to enable Ads modelers to drive unparalleled impact through scaled, agile machine learning. This requires working with collaborators across hardware, AI2, GDM, Research, Core Data, and others to ensure Ads' requirements are prioritized, and building what's needed on top of that to support our modeling and product teams.

Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

Responsibilities

• Manage the end-to-end Machine Learning development lifecycle, from experimentation to continuous self-improvement, to accelerate modeling Research and Development (R&D) velocity across AdsML.
  
• Partner with modeling, infrastructure, and research teams to drive long-term Ads business objectives.
• Lead the adoption of agentic engineering tools for model development, focusing on multiplying developer velocity and establishing guardrails.
  
• Govern development and execution of feature planning, prioritization and operations in AdsML.
  
• Evaluate team progress and risks in order to manage executive stakeholder expectations.