Machine Learning Engineer - News, Books, and Stocks Team

In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of machine learning. Our lively and brilliant distributed team consists of client and machine learning engineers who embody Apple's values. We inspire, teach, and otherwise enable each other to do the best work of our careers! Our team's outstanding retention rate speaks to our strong culture of respect for our teammates as both engineers and people. Would you like to work on such a team, solving hard problems in machine learning? Terrific! Please join us for the next generation of these apps! DESCRIPTION Our team is seeking a high-energy and self-driven machine learning engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle difficult and complicated problems in the news, books, and stocks domains, including text extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a member of our dynamic group, you’ll have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of Apple’s customers every day! MINIMUM QUALIFICATIONS MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable. Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar. Ability to communicate effectively and collaborate with partner teams. Commitment to encouraging an open and inclusive work environment. PREFERRED QUALIFICATIONS Ph.D. in Machine Learning, Computer Science, or related field. At least 2 years of experience shipping machine learning models in products. Experience with recommender systems. Experience with text-centric AI/ML (LLMs, document classification, search, etc.) Experience delivering high quality software at scale. Experience designing user-facing machine learning features with interdisciplinary partners. #J-18808-Ljbffr Socket.dev