At Apple intelligence begins with connection between data ideas and us in building the Knowledge Graphs and Agentic AI systems that bring those connections to life powering how millions experience the worlds 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. Youll 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.
Required Experience:
Senior IC
At Apple intelligence begins with connection between data ideas and us in building the Knowledge Graphs and Agentic AI systems that bring those connections to life powering how millions experience the worlds music books and podcasts!As a lead-level AI/ML Engineer you will drive the development and...
At Apple intelligence begins with connection between data ideas and us in building the Knowledge Graphs and Agentic AI systems that bring those connections to life powering how millions experience the worlds 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. Youll 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.
Required Experience:
Senior IC
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