Senior AI/ML Engineer, Media Understanding
Cupertino, CAFull-timeSeen 1w agoSeen in employer's feed 1 day ago
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Job overview
Apple’s Media Understanding team builds AI/ML systems that interpret media and relationships among content for Apple Music, Podcasts, TV, and Sports. The Cupertino-based engineer will partner with engineering, product, and design teams across Apple Services, help shape cross-team direction, represent the team’s work, and remain technically engaged with its systems. The role connects teams across sites and time zones.
Skills & qualifications
Skills
Qualifications
Full job description
Weekly Hours: 40
Role Number: 200669693-0836
Summary
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you can accomplish.
Our team builds the systems that help Apple understand media: what a song, episode, show or game is about, how pieces of content relate to each other, and how that understanding can power great experiences across Apple Music, Podcasts, TV and Sports. It's rigorous AI/ML work in a domain that's all about culture, storytelling and taste.
Much of the team is based in Barcelona, as part of a wider engineering group headquartered in Cupertino. We're looking for an experienced engineer in Cupertino to be the team's technical presence there: working day to day with partner teams in their timezone, joining the conversations where direction gets set, and bringing what you learn back into the team's work.
Description
You'll work closely with engineering, product and design partners across Apple Services, from early design discussions through to delivery. Some days you'll be deep in a partner team's systems working out how our capabilities fit; other days you'll be helping shape a cross-team plan or representing the team's work to leadership. You'll stay technically close to the team's own systems, because the role works best when you know them well.
It suits someone who enjoys connecting teams and shaping direction as much as building, and who likes working across sites and timezones.
Minimum Qualifications
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BS in Computer Science or a related field, or equivalent practical experience. MS or PhD in Computer Science, ML or a related field preferred.
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At least 8 years experience building and shipping production ML or large-scale software systems.
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Experience working across teams and influencing technical decisions beyond your own team.
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Clear written and confident verbal communication with both engineers and leaders.
Preferred Qualifications
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Experience with multimodal understanding, generative AI, knowledge graphs or semantic search.
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Experience with media content or catalogs.
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Familiarity with Apple Services teams and systems.
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Experience working with distributed teams across timezones.
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.
How this job compares
Set against the 546 open AI/ML Engineer jobs on Olive Jobs, counted November 12, 2026.
- Pay
- This postingNot listed
- California median$152–260K/yr49 salary ranges
- US median$26–67/hr36 hourly ranges
- Openings
- Olive Jobs lists 70 open AI/ML Engineer jobs in California and 546 across the US. 6% of them nationwide are listed as remote or flexible.
- Hiring the most in California
- Accenture14 open
- General Motors9 open
- Apple (this employer)6 open
- Experience
- This posting asks for at least 8 years of experience — more than three in four AI/ML Engineer postings that state a minimum ask for (median 5 years, across 495 postings).
- Education
- 224 of the 546 open AI/ML Engineer jobs (41%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 12, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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