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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer, Apple Store Online - **Company:** Apple Inc. - **Location:** Austin, TX, United States - **Experience:** Experienced - **Salary:** $129,300.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Big Data, C++ (Programming Language), Distributed Systems, Apache Hadoop, Python (Programming Language), Machine Learning, Natural Language Processing, Object-Oriented Software Development, Recommender Systems, Tensorflow, Software Engineering, SQL Databases, Reinforcement Learning, Feature Engineering, Pytorch, Snowflake, Apache Spark, Deep Learning, Generative AI, Keras, Information Technology, Machine Learning Operations, Data Pipelines - **Published:** September 1, 2026 - **Apply:** https://www.themuse.com/jobs/apple/machine-learning-engineer-apple-store-online-167b4b ## About the Role 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., Understanding of machine learning model lifecycle from prototyping, feature engineering, training, inference, deployment, monitoring and continuous improvements via deep analysis) Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture 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 Skilled in communication, problem solving, strategic thinking Minimum Qualifications Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems Hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc) Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, Statistics, or Bachelors degree in quantitative field with a focus on AI in coursework ## 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, 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 ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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