Principal Product Manager, Ads Delivery & Optimization

Nextdoor

1d•$200,000 - $335,000•Hybrid

About The Position

The Monetization Team at Nextdoor empowers businesses of all sizes to connect meaningfully with their local communities. Our advertising platform helps marketers reach the right audiences, drive measurable outcomes, and scale their growth efficiently. As a Principal Product Manager, Ads Delivery & Optimization, you will lead the strategy and roadmap for how campaigns turn advertiser goals into effective delivery and measurable outcomes. You will own bidding, pacing, ranking, outcome optimization, and the measurement foundations that make these systems reliable. This is a highly technical and strategic role at the center of Nextdoor’s Ads ecosystem. You will partner with Engineering, Machine Learning, Data Science, Revenue, Finance, and Product Marketing to evolve our auction, bidding, pacing, ranking, measurement, and ML-driven optimization systems. Your work will span platform capabilities and optimization products, directly impacting advertiser outcomes, revenue growth, delivery efficiency, and the neighbor experience. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London.

Requirements

12+ years of product management experience, including significant experience in advertising technology, marketplace optimization, or ML-driven ranking and delivery systems.
Deep expertise in ads delivery and optimization, including auctions, bidding, budget pacing, ranking, conversion optimization, attribution, or experimentation.
Strong technical fluency and experience partnering with Engineering, Machine Learning, and Data Science on models, experimentation, calibration, serving systems, and platform architecture.
Strong product judgment and experience balancing advertiser outcomes, revenue, delivery, measurement quality, and user experience when data or signals are imperfect.
Experience translating complex ML, automation, and infrastructure capabilities into intuitive advertiser products that drive measurable value and adoption.
Demonstrated ability to set strategy, lead complex initiatives across teams, influence senior stakeholders without formal authority, and communicate technical concepts clearly.

Nice To Haves

Experience with performance advertising, auto-bidding, privacy-constrained attribution, mobile measurement, or ML-powered products at scale is a plus.

Responsibilities

Own the strategy, roadmap, and execution for Ads Delivery and Optimization across auctions, bidding, budget pacing, ranking, conversion optimization, and automation.
Partner with Engineering, Machine Learning, and Data Science to define model objectives, design experiments, and drive deployment, monitoring, and iteration.
Expand optimization across advertiser goals, formats, and surfaces, including clicks, leads, purchases, app installs, video, Search Ads, SMB products, and emerging inventory.
Build the measurement foundations that make optimization reliable, including attribution, event and label quality, calibration, reporting, and privacy-constrained signals.
Turn complex optimization capabilities into intuitive advertiser products, including auto-bidding and other automation that improves outcomes and simplifies campaign management.
Drive tradeoffs across advertiser performance, revenue, delivery efficiency, platform investment, and the neighbor experience.
Align senior stakeholders on strategy, decisions, risks, and performance.