Apple Music - Machine Learning Engineer (Personalized Stations and Mixes)

The Music ML team at Apple Services Engineering is looking for a great Software Engineer to build and improve the features and services driving Apple Music personalization. This role is responsible for providing personalized features for Apple Music, including high-traffic surfaces such as Home, Radio, and Personal Mixes. The work involves building and maintaining ML-backed high-throughput online services, online experimentation and data analysis, as well as large-scale offline big data pipelines.

Key responsibilities include:

• Building products and services for millions of users with a focus on great customer experience and privacy
• Developing complex systems that integrate data from many sources to deliver on-the-fly personalization at low latencies
• Improving the quality of personalized music streaming experiences
• Working with ML researchers to take new user-facing features from conception to production
• Developing and deploying massive datasets to improve personalized features
• Prototyping algorithm changes and launching A/B tests to measure changes to personalized products

The ideal candidate will have a BS or MS degree in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, with a proven track record of collaborating with ML researchers to develop and improve highly scaled, ML-backed products. Strong programming skills in at least one modern object-oriented language (Java, Python, C++) and the ability to excel in a multi-functional environment are essential.

Apple offers a competitive compensation package, including base pay between $175,800 and $312,200, depending on skills, qualifications, experience, and location. Employees also have opportunities to become Apple shareholders through stock programs and are eligible for comprehensive benefits, including medical and dental coverage, retirement benefits, and education reimbursement.

Join the Music ML team at Apple and help shape the future of personalized music experiences for millions of users worldwide.