Description
As an engineer on the Apple Intelligence Data Platform team, you will work on developing and integrating foundational components for on-device and cloud-based intelligence. You will focus on designing, building, and deploying scalable agent systems that understand the user’s context and personal knowledge. Your work will directly influence how users interact with Apple products through on-device search as well as through context-aware, proactive, and personalized experiences. You will work on building the foundational platforms that personalize the on-device Siri assistant and sync the Siri and Apple Intelligence experience across the Apple device lineup — including iPhone, iPad, and Mac. This role is ideal for candidates with hands-on experience in Vector databases, Knowledge Graphs, Semantic Search, Retrieval-Augmented Generation (RAG), decoding strategies, Generative AI inference, and prompt optimization. You will collaborate closely with several engineering teams at Apple —such as Accessibility, Hardware, Human Interface, NLP, Privacy, etc- to power exciting Apple Intelligence features and ship them to our customers.
Minimum Qualifications
5+ years of increasing responsibility and relevant experience Bachelor's degree or higher in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Information Retrieval or a related field. Experience in building on-device platforms, data pipelines and frameworks. Experience in one or more of the following: Knowledge Graphs (KG), RAG systems, integration of LLMs with external memories, Vector databases and related fields. Experience supporting data analytics and instrumentation for large-scale ML / AI systems Deep understanding of machine learning and deep learning algorithms Experience designing and optimizing runtime or inference systems for machine learning and deep learning models in production Excellent software design, problem solving, critical thinking and collaborative skills including written and verbal communication Proficiency in one or more of the following languages: Python, Go, Java, C++, or Swift Ability to understand/clarify product requirements and translate them into technical tasks in ML modeling and engineering
Preferred Qualifications
MS or Ph. D in Computer Science or a related field Experience in LLM, machine learning models, deep learning models, information retrieval, platform development, or natural language processing Experience building offline experimentation, training, and evaluation pipelines to iterate on ML model performance and accuracy Strong analytical and independent problem-solving skills Experience working in cross-functional teams across product, design, and infrastructure
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