Senior Machine Learning Engineer Cambridge,Massachusetts,United States Corporate Functions Imagine what you could do here! The people here at Apple don’t just create products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work. Here on the Apple Store Online team, we are responsible for Apple’s largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things. We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will lead the way on our Online Retail Decision Automation team by researching and developing the next generation of algorithms used to drive the Apple Online experience! The role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimizing Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to be part of new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers every day. **Description** To be successful, candidates will need a strong machine learning background, proven software development skills, a love of learning, and to collaborate with cross-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to develop and implement machine learning algorithms. Mentor other MLE’s and lead an effort to build scalable end-to-end machine learning solutions for our retail customers. RESPONSIBILITIES INCLUDE: - Ability to build performant production applications with high through put. - Reading academic papers, apply novel ideas to our problem space and present to stakeholders. - Provide mentorship and guidance to other machine learning engineers and staying up-to-date with the latest advances in machine learning and software engineering. - Contribute to the ongoing improvement of our ML infrastructure and tooling, ensuring that we stay at the cutting edge of industry practices. **Minimum Qualifications** + 10+ years of related experience, including 5+ years experience in machine learning. + Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems. + End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc). + Deep understanding of machine learning model lifecycle from prototyping, feature engineering, training, inference, deployment, monitoring and continuous improvements via deep analysis). **Key Qualifications** **Preferred Qualifications** + Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience. + Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture. + Skilled in communication, problem solving, critical thinking. + Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus. + Experience with Spark, TensorFlow, Keras, and PyTorch a plus. **Education & Experience** **Additional Requirements** + Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) **Apple Footer** Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (Opens in a new window) . Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) . Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area. Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) . Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) . Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .