ML Engineering Manager - App Store Search
Apple
Software Engineering, Other Engineering, Data Science
San Francisco, CA, USA
USD 198,300-342,800 / year + Equity
Posted on Dec 12, 2025
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.
As the ML Engineering Manager for App Store Search, you will lead the design and evolution of the core systems that power Apple’s search, personalization, and agentic experiences. Your team will own the architecture, protocols, data flows, indexing, serving, inference, and automation, that ensures these systems are fast, reliable, and built for scale. You will drive the creation of new online and offline components using SOTA technologies, building first ML models where needed or partnering with the Relevance Intelligence team for more advanced iterations. Your leadership will shape the foundation that enables world-class search and agent experiences across Apple products. You will partner closely with product, data science, EPM, and, AB Test teams to ship fast, relevant, and trustworthy results that millions of users rely on every day.
- Own the architecture and technical direction for search, personalization, agentic systems, and internal tooling.
- Define and implement core system components, including protocols, data flow, indexing, serving, inference, and automation.
- Lead development of new systems, both online and offline, using state-of-the-art technologies, algorithms, and ML models.
- Build ML models when appropriate, or collaborate with the Relevance Intelligence team for deeper model development.
- Partner closely with product, infrastructure, and cross-functional teams to ensure system robustness, scalability, and long-term evolution.
- Develop and mentor a high-performing engineering team with strong fundamentals and a bias for impact.
- Deliver reliable, production-ready systems with clear execution focus, technical rigor, and user-centered design.
- 5+ years leading engineering teams delivering large-scale distributed systems, backend infrastructure, or search platforms.
- MS or Ph.D. in Computer Science, Machine Learning, Information Retrieval, or a related field.
- Experience building complex systems involving indexing, retrieval, serving, data pipelines, or ML-driven components.
- Strong execution record across the full engineering lifecycle.
- Expertise in large-scale search systems, ranking/retrieval architectures, personalization pipelines, or agentic system design.
- Experience building production ML systems or bootstrapping first version of ML models.
- Strong systems engineering fundamentals, APIs, protocols, distributed systems, data modeling, performance, and reliability.
- Ability to lead cross-functional alignment and balance long-term platform strategy with fast iteration.
- Effective communication and leadership skills; able to drive clarity, prioritize well, and develop engineering talent.
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