Senior Machine Learning Engineer - Knowledge Graph
About The Position
We are the Knowledge Graphs team at Apple building the intelligence layer that connects Apple's media ecosystem. We construct the single source of truth for Apple's content metadata - modeling and canonicalizing millions of entities across Music, Books, and Podcasts into richly connected knowledge representations that power search, discovery, personalization, analytics, and editorial experiences across Apple Services. As part of Apple Service Engineering, we operate at global scale, blending art and technology to deliver extraordinary experiences across Apple Music, App Store, Apple TV, Apple Fitness+, Apple Podcasts, and Apple Books-serving hundreds of millions of users in 175+ countries and 37+ languages. We're looking for an accomplished Machine Learning Engineer with a deep passion for Knowledge Graphs and Agentic AI systems to help shape how we understand and organize the world's creative works. If you're inspired by the challenge of transforming complex, messy data into connected, intelligent systems that can reason, adapt, and evolve-we'd love to work with you! At Apple, intelligence begins with connection - between data, ideas, and people. Join us in building the Knowledge Graphs and Agentic AI systems that bring those connections to life, powering how millions experience the world's music, books, and podcasts!
Requirements
- Experience with large-scale data pipelines, distributed model training, or feature engineering systems.
- Familiarity with multimodal learning, ontology management, or data governance.
- Proven ability to align AI innovation with product and user impact.
- Passion for human-centered AI that balances creativity, privacy, and intelligence.
- Curiosity about emerging paradigms in self-organizing AI systems and autonomous knowledge representation.
Responsibilities
- As a lead-level AI/ML Engineer, you will drive the development and scaling of knowledge graph intelligence and agentic AI systems at Apple.
- You'll architect the models, pipelines, and reasoning frameworks that turn billions of metadata records into a cohesive, adaptive source of truth.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Industry
Computer and Electronic Product Manufacturing
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
