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ey 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: - Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment. - Contribute to the ongoing improvement of our ML infrastructure and tooling. - Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering.
Minimum Qualifications
3+ years of related experience building high throughput scalable applications or building machine learning models.
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems.
Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc.
Skilled in communication, problem solving, strategic thinking.
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.
Additional Requirements
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