The future of personalization is private, and it lives on the device. Our team builds the intelligent features for the App Store, Apple Music, and Apple TV+ that reach millions of users, and we do it with an unwavering commitment to user privacy.
Description
We are seeking a skilled engineer to solve one of the most challenging and important problems in tech today: how to build deeply personal and helpful AI systems that are private and compliant by design. You will be a key contributor to this mission, architecting and implementing on-device ML solutions that not only delight users but also set the industry standard for trust and security.
This is a hands-on role where you will write code in Swift, optimize models for the edge, and serve as a crucial link between our machine learning ambitions and our core privacy values.
Minimum Qualifications
BS or MS in Computer Science, Statistics, or a related field, preferably with a focus on machine learning or data privacy.
Experience Level: A minimum of 3 years of professional software engineering experience, with a track record of shipping production code.
Strong Systems Programming: Strong proficiency in Swift and/or C++, with hands-on experience building for Apple platforms.
Production ML Experience: Practical experience developing and deploying machine learning models in a production environment (on-device or server-side).
Passion for Privacy: A demonstrated passion for and understanding of user privacy, data security, and the engineering challenges related to building trustworthy systems.
Preferred Qualifications
Generative AI / Agentic Systems Experience: Proven experience architecting or building with Generative AI (LLMs, Diffusion Models) or agentic systems.
Compliance Engineering Experience: Deep experience translating legal and policy requirements from regulations like GDPR and CCPA into concrete engineering designs and auditable systems.
On-Device ML Expertise: Direct experience with Core ML and on-device model optimization techniques (e.g., quantization, pruning).
Privacy-Enhancing Technologies: Familiarity with technologies like Differential Privacy or Federated Learning.
Responsibilities
Architect Private AI Systems: Design, build, and ship production-grade, on-device machine learning systems in Swift, using frameworks like Core ML.
Solve for Privacy and Compliance: Take a leading role in translating complex user privacy principles and global legal regulations (e.g., GDPR, CCPA) into concrete, auditable engineering solutions. Your work will be fundamental to our compliance strategy.
Obsess Over Performance: Write highly efficient, resource-conscious code, mastering the trade-offs between model performance, battery life, and memory footprint on mobile devices.
End-to-End Ownership: Take ownership of the full on-device ML lifecycle, from model quantization and deployment to performance monitoring and updates in the field.
Collaborate and Lead: Partner with backend ML teams, legal and policy experts, and application developers to build cohesive, privacy-first experiences.
Eeo Content
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
