Apple Ads Marketplace Product Manager - Ad Matching & Retrieval

At Apple, we work every day to create products that enrich people’s lives. The

App Store and Apple Maps are trusted destinations for millions of users to

discover apps, places, products, and services. Our advertising platform connects

users with high-utility advertiser offerings while maintaining Apple’s

uncompromising commitment to user privacy. The Apple Ads Marketplace team is

seeking an experienced, deeply technical Product Manager to drive the next

generation of our ad matching, search intent, and retrieval platform. In this

role, you will define the product strategy and roadmap for how we match user

intent to relevant advertiser offerings across the App Store, Apple Maps, and

emerging search and conversational surfaces. You will partner closely with

world-class ML research and engineering teams to build, train, fine-tune, and

inference cutting-edge machine learning and Large Language Model (LLM) systems

at massive scale.

DESCRIPTION

As the Product Manager for Ad Matching & Retrieval, you will shape how users

discover relevant apps and services across Apple’s ecosystem: - Pioneer Next-Gen

Ad Matching with LLMs: Lead the strategy to train and deploy transformer and

LLM-based models for semantic matching, query intent extraction, query

rewriting, and keyword-to-ad relevance across billions of daily requests. -

Advance Multi-Surface Search Retrieval: Expand retrieval capabilities across the

App Store, Apple Maps, and conversational surfaces, ensuring high recall of

high-utility ads tailored to diverse user contexts. - Scale Real-Time & Offline

Inference: Collaborate with client and server ML engineering teams to optimize

retrieval pipelines to enable embedded based retrieval, keyword generation, ANN

vector search, candidate pruning, while keeping to a strict serving latency. -

Own the Matching Product Roadmap: Define the vision, key metrics (retrieval

recall, coverage, CTR impact, advertiser ROI), and execution milestones for

auto-targeting, and both lexical and semantic intent features. - Leverage

Cross-Functional Apple Signals: Partner with teams across Apple to ethically

integrate privacy-preserving signals, platform ontologies, and catalog

embeddings to continuously enrich match quality. - Data-Driven Strategy & Deep

Dives: Analyze marketplace health, auction drop-offs, and query coverage to

uncover gaps and inform future modeling directions.

MINIMUM QUALIFICATIONS

3+ years of technical product management experience, owning the full product

lifecycle from concept to launch for machine learning or advertising systems.

Hands-on experience with AI/ML systems, with an emphasis on training,

fine-tuning, evaluating, and inferencing large-scale deep learning models and

LLMs. Strong domain knowledge in search, information retrieval, or ad matching,

including keyword expansion, semantic search, vector embeddings, dense retrieval

(e.g., bi-encoders, ANN indexing), and query understanding. Experience with

high-throughput, low-latency online inference architectures across client and

cloud server environments. Strong technical and analytical foundation, including

deep proficiency with SQL and data exploration in large-scale data warehouses.

Outstanding written and verbal communication skills, with proven ability to

translate complex AI/ML architectures into crisp PRDs, system diagrams, and

executive strategy. Demonstrated leadership and cross-functional influence,

adept at aligning engineering, applied research, business, and design

stakeholders without formal authority. Bachelor’s or Master’s degree in Computer

Science, Electrical Engineering, Machine Learning, Data Science, or equivalent

practical experience.

PREFERRED QUALIFICATIONS

Experience building ad marketplace matching retrieval systems, including

auto-targeting, keyword targeting, and keyword generation. Practical

understanding of multi-modal search and graph-based retrieval across diverse

catalog types (e.g., App Store apps, Maps points of interest, local business

entities). Track record of designing and running large-scale online A/B

experiments for marketplace optimization.