ML Engineering Manager - App Store Search Relevance

The Apple Services Engineering (ASE) team is one of the most exciting examples of Apple's long-held passion for combining art and technology. These are the people who power Search for the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And they do it on a massive scale, meeting Apple's high expectations with high performance to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. These engineers build secure, end-to-end solutions. They develop the custom software used to process all the creative work, the tools that providers use to deliver that media, all the server-side systems, and the APIs for many Apple services. Thanks to Apple's unique integration of hardware, software, and services, engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, nimble, and cross-functional, offering greater exposure to the array of opportunities here.

Description

As the ML Engineering Manager responsible for Quality of Search Results, Autocomplete and QnA systems, you will lead a Relevance Intelligence team advancing the ranking, personalization, and LLM-driven systems that power Apple's search and discovery experiences. Your team will drive continuous hillclimbing, fine-tuning, and rapid iteration across key quality surfaces while owning the model-training platform that delivers these improvements at scale. You will partner closely with product, data science, EPM, and, AB Test teams to ship fast, relevant, and trustworthy search results that millions of users rely on every day.

","responsibilities":"Lead hillclimbing/quality improvement and fine-tuning across core quality areas: Search & Autocomplete Ranking, Search Personalization, Spam detection, Query Understanding, Retrieval Agents

Own and evolve the model-training system, spanning data pipelines, evaluation, and production workflows.

Partner with XF teams to align goals, unblock training needs, and accelerate quality improvements.

Drive pragmatic, production-ready use of SOTA ML and LLM models.

Build, mentor, and develop a high-impact engineering team.

Provide clear technical direction and operational excellence across multiple quality streams.

Preferred Qualifications

Expertise in ranking, retrieval, LLM fine-tuning, personalization, and search quality.

Experience with hillclimbing, iterative evaluation, and high-throughput training pipelines.

Strong engineering leadership with a focus on clarity, execution, and impact.

Ability to align cross-functional teams and balance long-term vision with rapid iteration.

Minimum Qualifications

5+ years managing engineering or AI/ML teams working in NLP, LLMs, ranking, or search systems.

MS or Ph.D. in Computer Science, Machine Learning, Information Retrieval, or related field.

Strong delivery record across the full AI/ML lifecycle.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .