Apple Media Products (AMP) - Machine Learning Engineer
London, Greater London, United Kingdom
Software and Services
Would you like to help us bring surprise and delight to the experience of tens of millions of Apple Music subscribers and to influence the future development of Apple products? The team behind many of the key features of Apple Music is looking for a talented machine learning engineer to help build our next generation of recommendation and playlisting services. You'll be joining a small and enthusiastic group of researchers and developers who share a real passion for science, engineering and music, and who care tremendously about our central mission of connecting artists and music lovers.
- proven knowledge of applied machine learning
- strong software development skills in Python
- experience in an object-oriented language such as Java, Scala or C++
- familiarity with current ML toolkits such as TensorFlow or PyTorch
- strong written and oral communication skills
- love of music
In this role you will be joining a cross-functional team of researchers and engineers to work on challenging problems in applied machine learning, ranging from audio content-based analysis to recommender systems for music. Engineers on our team are expected to contribute to all parts of our research and development process, working on data processing pipelines, algorithm design and prototyping, implementing solutions at scale in a production environment, tracking metrics and reporting results. To thrive in this role you'll need proven software development skills, a scientific mindset with a strong appetite for learning, and an ability to communicate well with a variety of colleagues in a dynamic environment. In return you'll have the chance to work with state of the art resources at Apple, including huge compute grids, top-quality machine learning tools, and massive quantities of data. Based in central London, you will also occasionally travel internationally to work with other teams at Apple, particularly in the US. Is this you? If so we'd love to hear from you.
Education & Experience
- BS or MS in computer science, statistics, applied mathematics or related field.