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Job Description
Weekly Hours: 40
Role Number: 200648838-0836
Summary
The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.
Apple Music touches millions of lives every day. We’re looking for an experienced, hands-on Lead AI Product Manager to help shape the next generation of personalized, intelligent music experiences. In this role, you’ll focus on building and shipping AI-powered features that make Apple Music more intuitive, relevant, and deeply personal for every listener.
You’ll work at the intersection of product, machine learning, data science, and design to bring innovative personalization capabilities to life — with a relentless focus on the customer experience.
Description
As a Lead AI Product Manager on Apple Music, you will own key global product experiences across AI and personalization, including recommendations, search relevance, user modeling, content discovery, and generative AI–powered features. You’ll translate broader strategy into clear product requirements and drive execution from concept through launch and iteration.
This is a senior individual contributor role. You will partner closely with engineering, design, editorial, business, analytics, and marketing teams to deliver high-impact features at scale.
Your responsibilities will include:
Defining product requirements and roadmaps for AI/ML-powered personalization experiences.
You will lead key product innovation which will different Apple Music even further.
Partnering with engineering and data science to develop scalable, privacy-conscious personalization systems.
Translating complex machine learning capabilities into intuitive, user-facing experiences.Synthesizing qualitative insights, quantitative analysis, and user research into clear product decisions.
Collaborating with central AI/ML platform teams to leverage shared infrastructure and capabilities.
Ensuring seamless integration of AI-driven features into the broader Apple Music experience.
Monitoring industry trends in AI, personalization, and consumer media to inform product direction.
Clearly communicating product strategy, tradeoffs, and results to stakeholders at multiple levels.
You’ll play a critical role in delivering meaningful improvements in engagement, retention, and long-term customer satisfaction.
Minimum Qualifications
5–7+ years of product management experience, including meaningful experience working on AI/ML or personalization-driven products.
Demonstrated experience shipping ML-powered consumer features at scale.
Strong understanding of recommendation systems, ranking systems, user modeling, and segmentation approaches.
Ability to work independently, drive clarity in ambiguous spaces, and manage complex cross-functional initiatives.
Excellent written and verbal communication skills, with the ability to tailor detail to different audiences.
Strong analytical thinking and structured problem-solving skills.
Passion for music and deep appreciation for Apple’s design and user experience principles.
Preferred Qualifications
Experience working closely and collaboratively with both design and engineering partners.
Strong analytical and problem-solving skills
Strong verbal and written communication skills to represent at all levels of the organization
Thrives in highly collaborative projects, effective at building consensus, handles decisions with ease, and has the ability to navigate ambiguity.
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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .
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