Description
We're looking for a Senior Machine Learning Engineer to help shape how Apple represents media knowledge and uses it to build rich, accurate, and personal experiences. You'll work at the intersection of large language models, information extraction, and knowledge graphs. You'll have end-to-end ownership of designing how knowledge is modeled, building the systems that produce it at scale, and ensuring its quality. You'll work closely with engineers and product partners, owning hard problems from early prototypes through to production.
Responsibilities
•Design expressive knowledge representations and build scalable systems that extract knowledge from large volumes of multimodal content (text, audio, and video).
•Define and own quality standards, combining human annotation and automated evaluation to continuously measure and improve system accuracy.
•Design and implement retrieval, reasoning, and discovery systems over large corpora of knowledge.
•Partner with product and engineering teams across Apple to take new media intelligence capabilities from initial prototype to production.
•Review designs, mentor engineers, and set technical direction.
Requirements
•B.S. in Computer Science, Machine Learning, Engineering, or related field, or equivalent practical experience.
•Substantial experience building and shipping large-scale ML/AI systems in production.
•Hands-on experience building production ML systems using LLMs, ideally for information extraction, entity linking or knowledge graphs.
•Strong programming skills, and experience building production streaming and batch data pipelines.
•Excellent communication and collaboration skills, with the ability to explain complex topics clearly.
Nice to have
•M.S. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related field.
•Experience designing knowledge representations, data models, or ontologies.
•Experience with multimodal understanding of audio, video, or images, such as speech recognition or video understanding.
•Experience with LLM-as-judge evaluation and running human annotation programs.
•Experience with vector search technologies, RAG, or LLM agents that use tools and multi-step reasoning.
•Experience with Spark or similar distributed data processing frameworks.
Conditions
No conditions were stated in the posting.
