Senior Data and Applied AI Engineer, Core Data & Intelligence

Summary

Imagine what you could do here. At Apple, new ideas become extraordinary products, services and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you can accomplish. Would you like to shape the future of Apple's products and platform, and impact some of the most far-reaching software in the world?

The Core Data & Intelligence organization builds the data, models and services that accelerate the growth of Apple's services. This role sits on the team focused on iCloud. We enable better products, features and infrastructure for iCloud users, who access all their content across apps (Photos, Mail, Messages, FaceTime, Calendar and more) from all their devices, all the time. We do that by providing consistent, scalable, timely, accurate, complete and fully integrated data infrastructure and capabilities that accurately surface relevant information.

We're looking for an exceptional Data and Applied AI Engineer with a strong background in distributed data processing, sharp and demonstrable data intuition, and a passion for using data to make Apple's products and platform better. If hard, high-leverage problems at scale energize you, we'd love to hear from you.

Description

You will build large-scale data pipelines and backend services, and partner closely with teams across iCloud to turn business needs into data solutions, iterating quickly at every stage of the pipeline. You will have real ownership and influence over the data platform that powers iCloud analytics and drives decisions across our products.

Who you are:

You are tenacious, relentless and determined.

You are curious: always learning new technologies, quickly synthesizing new information, and understanding the why before the what.

You turn vague requirements into scalable data solutions.

You care about excellence and enjoy picking up new technologies and frameworks.

Responsibilities

• Build distributed data systems. Design and build scalable, highly available systems for large-scale data processing and analytics that deliver consistent results for stakeholders.
• Put AI to work. Build LLM-powered applications and intelligent agents at scale that automate routine work and give stakeholders new capabilities.
• Protect privacy. Uphold Apple's core values by ensuring every system and solution meets Apple's privacy policy and data security standards.
• Own rich datasets. Curate and evolve extremely rich datasets on iCloud products and platform interactions to power a wide range of use cases.
• Build for the future. Design solutions that fit cleanly with existing systems, and use sound judgment to bring cutting-edge technologies to iCloud's needs.
• Raise the bar on quality. Understand complex systems, write clean and efficient code, and keep improving how we engineer software.
• Tie technology to outcomes. Understand how key technical decisions drive business results, and partner with cross-functional teams to deliver data frameworks and platforms that get there.

Minimum Qualifications

• 8+ years building efficient, large-scale data pipelines with Spark and other distributed data technologies (such as Hadoop, Presto, Flink or Druid).
• Highly proficient in at least one of Java, Python or Scala, with strong SQL skills.
• Deep expertise in data principles, data architecture and data modeling.
• Solid grasp of the data lifecycle, including lineage, governance, privacy, retention and anonymity.
• Hands-on experience working with LLMs and developing AI agents.
• Bachelor's degree in Computer Science or Engineering, or equivalent work experience in data engineering.

Preferred Qualifications

• Experience designing and building LLM-powered applications and intelligent agents at scale.
• Experience in a complex, matrixed organization on cross-functional or cross-business projects.
• Strong communication and collaboration skills, with the ability to lead discussions on technology strategy and approach.
• A track record of improving how an organization uses data.