Senior Machine Learning Manager - Apple Ads
Apple
Software Engineering
Cupertino, CA, USA
Posted on Jul 1, 2025
At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone! The Data Insights team within Apple Ads is seeking a bright and endlessly curious data expert to lead our Core Insights team that supports the organization. This individual will be responsible for leading a team that turns the huge amounts of data generated by user searches, app metadata, and App Store content into business insights that improve the customer experience for the end-user as well as drive discovery and productivity for app developers. We are seeking a self-motivated leader that can execute on near-term plans and contribute to defining a longer-term vision for our team and Apple Ads. This role involves working with internet-scale data across numerous product and customer touch points; undertaking in-depth, quantitative analysis on business performance; developing and running prediction and forecasting models; and building ML models including LLMs to drive core business decisions. The team’s culture is focused on rapid iteration with open feedback and debate along the way, plus strong collaboration with product, engineering, business, and marketing partners. You will have experience hiring and leading large-scale, sophisticated data science teams that deliver impactful insights via pattern mining, anomaly detection, modeling, classification, and creation of wide ranging analytical tooling. Successful candidates will take pride in implementing and sustaining end-to-end analytical solutions that have direct and measurable impact. The role requires both a broad knowledge of existing data mining algorithms and creativity to invent and customize when necessary.