Machine Learning Engineer - System Experience, Proactive

Summary

The Agentic Search team creates the next generation of intelligent, on-device search experiences across Apple products. In this role, you will collaborate with machine learning, app engineering, and infrastructure teams to build responsive, personalized capabilities powered by agentic technologies. You will partner across the company to design features that balance advanced intelligence with Apple's commitment to user privacy.

Minimum Qualifications

Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience. 4+ years of application development experience with Swift, Objective-C, or an equivalent high-level programming language on iOS or macOS. Experience developing search systems, including indexing and retrieval technologies. Experience collaborating cross-functionally and communicating technical concepts to diverse teams.

Preferred Qualifications

Experience designing public or system-level APIs and developer frameworks. Experience profiling, diagnosing, and optimizing system-level mobile software performance. Familiarity with machine learning principles or large language model fundamentals.

Description

As a Machine Learning Engineer on the System Experience team, you will integrate personal search technologies directly into applications across Apple platforms. You will design durable, reusable architectures and public-facing interfaces for third-party developers, incorporating data across multiple systems while upholding on-device privacy standards. This role requires close cross-functional partnership with OS framework, machine learning, and services teams to optimize system performance and tailor intelligent features for every Apple device.

Responsibilities

Integrate on-device personal search technologies with system applications across iOS, macOS, and other Apple platforms. Design and build reusable software architectures, frameworks, and developer-facing APIs built for long-term scalability. Partner with cross-functional machine learning, OS framework, and services teams to adapt and optimize technologies for mobile constraints. Incorporate multi-system data streams into unified search experiences while safeguarding user privacy on-device. Balance system trade-offs, profiling, and runtime performance to deliver responsive user experiences.