AI/ML Program Manager — Ads Platform & User Experience

Google; Mountain View (CA); On-site; USD 132,000 - 189,000; Full time

Job summary

Google Ads is seeking a Program Manager II for AI/ML in Mountain View to lead complex, multi-disciplinary initiatives across Ads, Search, and AI experiences. You will plan requirements, manage schedules, identify risks, and coordinate cross-functional partners across offices and time zones to deliver high-impact ads improvements.

The role emphasizes integrating personalized signals and lightweight models to reduce low-quality ads while maintaining monetization and user trust, with equity and

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 (e.g., real-time model serving, teacher-student distillation, contextual signals).

Responsibilities

• Drive cross-functional planning, tracking, and execution across multiple core projects.
• Lead program delivery for integrating personalized intent signals into auctions to mitigate bad ad experiences.
• Manage deployment of lightweight student models to scale real-time user-context encoders and filtering.
• Roll out launches and brand protection rules with partner teams to reduce scammy and low-quality ads.
• Oversee joint technical roadmaps and risk mitigation with multiple AI/Ads partners.

Skills

Program management

Cross-functional collaboration

Mentoring junior teammates

Stakeholder communication

Education

Bachelor's degree or equivalent

Tools

LLM interfaces

AI/ML tooling

Job description

Google Ads is seeking a Program Manager II for AI/ML in Mountain View to lead complex, multi-disciplinary initiatives across Ads, Search, and AI experiences. You will plan requirements, manage schedules, identify risks, and coordinate cross-functional partners across offices and time zones to deliver high-impact ads improvements.

The role emphasizes integrating personalized signals and lightweight models to reduce low-quality ads while maintaining monetization and user trust, with equity and