At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. If you are an ambitious, high-energy individual who is not afraid of challenges, we’re looking for you.
Apple is seeking an expert Machine Learning Engineer or Applied Scientist to join a team passionate about building ML models for the media space, covering services such as Apple Arcade, Apple Music, and Apple TV+.
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 team’s culture is centered around rapid iteration with open feedback and debate along the way. We encourage independent decision-making and taking calculated risks. AMP Data Science collaborates with partners across product, design, engineering, and business teams: our mission is to drive innovation at Apple through deep quantitative research.
Collaborate with Apple Media Products stakeholders and partners to design Machine Learning models that help us better understand and serve our customers, primarily focusing on the App Store, and extending to additional Services such as Apple Arcade, Apple Music, and Apple TV+. Engineer end-to-end Machine Learning products which provide Apple with a granular understanding of customer preferences and user value drivers, including scalable solutions for customer acquisition 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 the App Store and other 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. This position is based in Culver City.