Senior Machine Learning Engineer - Knowledge Graph
Apple
Full-time
On-site
Seattle, Washington, United States
Machine Learning
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!
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.
- 10+ years of experience in machine learning or applied AI, including at least 2+ years in a technical or team lead role.
- Proven success leading end-to-end ML projects from research through deployment.
- Demonstrated experience in supervised and RL model training, fine-tuning, and distillation.
- Demonstrated experience with Agentic AI systems — building multi-agent workflows, LLM-based orchestration, or autonomous reasoning pipelines.
- Demonstrated experience in Knowledge Graph construction, entity resolution, or semantic reasoning.
- Strong expertise in ML frameworks such as PyTorch, Hugging Face, LangGraph, or equivalent.
- Strong foundation in deep learning, NLP, and Generative AI (fine-tuning, RAG, and prompt-based orchestration).
- Deep proficiency in Python, with working knowledge of Java, Scala, or Go.
- Excellent communication and cross-functional collaboration skills.
- M.S. or Ph.D. in Computer Science, Machine Learning, or related technical field.
- Experience with distributed ML frameworks such as Ray, large-scale data pipelines, 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.