Program Manager II, AI/ML, Google Ads

Drive cross-functional planning, tracking, and execution across multiple core projectsLead program delivery for integrating personalized intent signals (pGood, pRel, pContext) directly into Text and PLA auctions to mitigate bad ad experiences before serving.Manage the deployment of lightweight student models distilled from massive LLM auto-raters to scale real-time user-context encoders and low-quality filteringWith partner teams, roll out significant launches and brand protection rules to achieve a reduction in scammy impressions and an overall reduction in low-quality adsOversee joint technical roadmaps and alignment with AI Experiences, Automation, Retail, and Ads UI partners, maintaining clear leadership tracking and risk mitigationMinimum qualifications:Bachelor's degree or equivalent practical experience.2 years of experience in program or project management.Experience integrating generative AI tools or LLM interfaces into workflows.Experience with Machine Learning projects (such as real-time model serving, teacher-student distillation frameworks, contextual user signals, etc.).Preferred qualifications:2 years of experience managing cross-functional or cross-team projects.Experience with Search, Ads, or large-scale AL/ML infrastructure projects.Experience driving joint roadmaps and dependency alignment across engineering, product management, and other partner teams.Ability to manage high-stakes OKRs, proactively mitigate risk, and streamline tracking across multi-workstream portfolios.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 Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines. The team is dedicated to delivering the optimal balance between monetization and user satisfaction by strategically selecting and presenting relevant ads. We use machine learning techniques, including Gemini/Agent, and meticulously measure and build solutions that enhance user sentiment in the presence of advertisements.As a Program Manager, you will drive a high-impact, cross-functional program aimed at fundamental improvements in user experience and ecosystem trust. You will lead strategic initiatives to reduce user toil through personalized sentiment launches and dramatically elevate Ads reputability by reducing egregious and low-quality ads.Your work will directly shape the quality, relevance, and safety of billions of daily search interactions—ensuring users receive delightful, safe, and helpful ad experiences while eliminating scam and deceptive content across global Search surfaces.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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $132000 - $189000 (USD) + 15% bonus target + equity + benefitsLearn more about benefits at Google.Bachelor's degree or equivalent practical experience.2 years of experience in program or project management.Experience integrating generative AI tools or LLM interfaces into workflows.Experience with Machine Learning projects (such as real-time model serving, teacher-student distillation frameworks, contextual user signals, etc.).