About the Role:

We’re looking for a Staff Product Manager, Ads Ranking & Personalization to define and lead the ML-driven ranking, targeting, and personalization systems that power Fetch’s ads business. In this deeply technical role, you’ll own the strategy and roadmap for how we match users to the most relevant ads and offers, optimizing for user experience, advertiser outcomes, and marketplace health.

With more than $180B in annual purchase data, Fetch has the scale and signal richness to build one of the most effective retail media personalization engines in the industry. You’ll shape how we leverage ML models, signals, and optimization frameworks across the full ads delivery pipeline, from eligibility and scoring to pacing and optimization.

You’ll partner closely with Engineering, ML, Analytics, and Sales to drive the company’s ads personalization strategy. As Fetch’s ranking and relevance leader, you’ll define how personalization is applied across every ad surface and deliver measurable impact to marketplace performance and revenue.

This is a critical leadership role within the Ads Product organization, with significant influence over the long-term direction of Fetch’s ads platform.

Responsibilities:

Own the vision, strategy, and roadmap for Fetch’s ML-driven ads ranking and personalization systems across all surfaces. Define the optimization framework balancing Fetch’s goals, advertiser objectives, and consumer experience ensuring ranking improves overall marketplace health. Design the architecture and boundaries between the ad server and ML systems, determining what logic, signals, and controls live in each layer and how they integrate end-to-end. Partner with cross-functional PMs to translate advertiser outcomes (e.g., reach, ROAS, purchases) into ranking objectives and optimization strategies. Lead the development of ranking models, signals, and infrastructure, including feature strategy, real-time scoring pipelines, and online/offline evaluation. Establish rigorous experimentation and evaluation frameworks, driving measurable improvement in relevance, personalization, and advertiser ROI. Collaborate deeply with Engineering, ML, Analytics, Sales, and GTM to prioritize, execute, and continuously iterate on ranking and personalization capabilities.

Minimum Requirements:

8+ years of product management experience building ML-powered ranking, personalization, recommendation, ads, or search systems.  Deep understanding of ML ranking, feature engineering, real-time scoring, user behavior modeling, and entity understanding (products, offers, merchants, categories). Experience in ads relevance, auction or bidding mechanics, targeting, or marketplace optimization is a plus.  Proven ability to set strategy, prioritize roadmaps, and drive measurable outcomes in fast-paced, ambiguous environments. Demonstrated strength in balancing competing objectives across a two-sided marketplace—optimizing for user experience, advertiser performance, and platform health. Strong technical fluency and ability to partner closely with Engineering, ML, Data Science, Analytics, Sales, and Marketing on data models, architecture, and trade-offs. A bias for ownership, rigor, and problem-solving able to dive deep into technical details while keeping focus on long-term impact.