Applied AI Engineer - iCloud Data

About the role

The iCloud Data organization within Apple Services enables iCloud users to access all their content across apps (Photos, Mail, Messages, FaceTime, Calendar, Enterprise & Education etc) on every device, all the time, through consistent, scalable, timely, accurate, complete and fully integrated data infrastructure that surfaces relevant information. We are investing deeply in a new generation of AI-native capabilities, agents, intelligent workflows, and self-serve analytics, to accelerate our Data Engineering and Data Science teams and define what an AI-first data organization looks like at Apple scale. If this excites you and you're energized by taking novel AI techniques from research to production on hard, high-leverage, high-scale problems, we'd love to hear from you! We're seeking a top-tier Applied AI Engineer with strong architectural thinking, deep AI/ML knowledge and robust software skills, who has built AI products end-to-end, has sharp intuition for LLMs, agents, retrieval and evaluation, and shares our passion for trustworthy data-driven products at Apple.

Responsibilities

• Design, build and own AI systems end-to-end, from retrieval, planning and reasoning, through evaluation, guardrails and observability, to deployment and the on-call rotation that keeps them trustworthy.
• Build deep domain expertise across our data and AI stack, product and business, and be an advocate for engineering excellence and responsible AI.
• Educate and uplevel the broader Data organization on modern AI patterns, running workshops, authoring technical playbooks and design guidance, mentoring engineers and scientists, and helping the team adopt AI-native practices that accelerate both the engineering and data science lifecycle.

Requirements

• Model and prompt customization at scale: fine-tuning foundation models, training reward models, building custom retrieval, reranking or embedding models for domain-specific tasks, and prompt engineering with performance, reliability and safety optimization.
• Experience with MLOps and LLMOps, model lifecycle management, deployment pipelines, observability, and prompt and evaluation versioning.
• Experience building natural-language interfaces over data, text-to-SQL, semantic search, or analytics copilots, for both internal and customer-facing use cases.
• Experience leveraging AI-native code editors and agent-assisted development environments to improve developer productivity, and establishing guardrails for their responsible use (security, IP protection, compliance, code quality).
• Experience with cloud computing platforms (AWS, Google Cloud, Azure) and stream-processing systems (Apache Flink, Spark-Streaming, Kafka Streams) for real-time data and real-time AI applications.
• Experience building AI solutions for machine learning, experimentation and responsible AI in regulated or privacy-sensitive environments. Contributions to open source, research, talks or technical writing that has shaped how others build AI systems.
• 8+ years of software engineering experience building scalable systems, reusable tools and frameworks, with 3+ years taking LLM or agentic systems from prototype to production, and deep fluency in the modern AI stack.
• Solid foundation in machine learning and deep learnin

Additional Information

Would you like to drive the future of Apple's data platform and shape how AI fundamentally transforms the way we build, operate, and scale data at Apple, while having the unique opportunity to impact some of the most far-reaching software applications in the world?

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