Senior Machine Learning Engineering Manager – Ads Predictions
Apple - Cupertino, United States of America
Posted Mar 26, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- Salary
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- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
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About this role
Senior Machine Learning Engineering Manager – Ads Predictions Cupertino, United States of America At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. We are looking for a leader with deep experience in Ad Tech who has built and scaled complex machine learning models in production. Preferably, you have a strong track record of delivering high-impact response prediction systems (e.g., click-through rate, conversion rate, post-conversion optimization) at scale, and understand the nuances of optimizing for user engagement, relevance, and long-term value under latency constraints. You bring hands-on experience developing and deploying large-scale models, with an appetite for pushing state-of-the-art techniques and advancing model capability through increased scale and complexity. You are motivated by privacy-preserving machine learning and have experience building systems that operate effectively within privacy-first constraints. In this role, you will lead the strategy and development of inference models that predict and optimize user interactions with ads, working across the full modeling stack-from data and model training pipelines to real-time serving and experimentation. You will
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