
Machine Learning Engineer
4 days ago
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. You 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 This 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 a new projects and craft upcoming products that will delight and encourage millions of Apple's customers every day.
Description
To be successful, you 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. You'll mentor other MLE's and lead an effort to build scalable end-to-end machine learning solutions for our retail customers
Minimum Qualifications
7+ 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
Skilled in communication, problem solving, strategic thinking
Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience
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
Experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc)
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems
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