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Machine Learning Engineer, Apple Media Products Data Science - Culver City, CA


  • python

Quick Facts

Culver City, CA, US

Job description

At Apple, phenomenal ideas have a way of becoming great products, services, and customer experiences very quickly. If you are a results-oriented, passionate individual who is not afraid of challenges, were looking for you.

Apple is seeking a specialist Machine Learning Engineer or Applied Scientist to join a team passionate about building ML models for the media space, covering the App Store, Apple Music, Apple TV, Apple Arcade, and other media services.

This role will involve working with Internet-scale data across numerous product and touch points and building/implementing products to drive business and marketing strategy.

The teams culture is centered around rapid iteration with open feedback and debate along the way. We encourage independent decision-making and taking calculated risks. AMP Analytics collaborates with partners across product, design, engineering, and business teams: our mission is to drive innovation at Apple through deep quantitive research of the App Store, Apple Music, Apple TV and Apple Arcade

Collaborate with Apple Media Products stakeholders and partners to design Machine Learning models that help us better understand and serve our customers across the App Store, Apple Music, Apple TV and Apple Arcade among other services.

Engineer end-to-end Machine Learning products which give Apple with a granular understanding of customer preferences and user value drivers, including scalable solutions for customer messaging and targeting!

Support engineering, business, and marketing teams at Apple in optimizing all customer touch points by detecting usage patterns with data-driven / machine-learned methods and translating them into actionable solutions.

Dive deep into large-scale data sources to uncover opportunities for Machine Learning automation, predictive methods, and quantitative modeling across Apple services.

Partner with other Apple organizations on data engineering, data governance, evangelizing Machine Learning, and democratizing data.

Increase internal adoption of ML and AI products.

Your creative problem solving skills will be utilized daily.
Apply now