Senior Software Engineer, On-Device Health Agentic Systems

What You'll Build: - AI-Powered iOS Applications: Architect and build innovative, high-performance on-device apps that showcase the power of intelligent LLM agents. - Scalable On-Device Architecture: Design the client-side frameworks and architectural patterns for integrating LLM systems efficiently on iOS. - LLM Agent Integration: Implement the software that connects user-facing applications to on-device and hybrid AI reasoning and planning engines. - Interactive AI Prototypes: Rapidly build and iterate on application prototypes to explore new user interactions and architectural options. Impact: This is a unique opportunity to define the future of intelligent applications at Apple. You will be at the center of building a new class of on-device experiences, setting the architectural foundation for how millions of users will interact with AI on a daily basis. Lead the development of sophisticated iOS frameworks and applications that integrate directly with on-device LLM systems on Apple platforms. Architect robust, scalable, and power-efficient software patterns for AI-powered features on iOS. Collaborate with ML and AI researchers to translate cutting-edge models into tangible application features. Implement and optimize the on-device components for LLM inference, context management, and tool execution. Drive the technical roadmap for on-device AI application architecture. 5+ years of professional software development with expert-level experience building high-performance, consumer-facing mobile applications and frameworks. Strong proficiency in a modern systems programming language such as C++, ObjectiveC/Swift, or Rust. A demonstrated ability to quickly master new languages and platforms is highly valued. Deep understanding of mobile system fundamentals: concurrency, memory management, and power optimization. Practical knowledge of how LLM-powered systems work, including prompt engineering, agent frameworks, or RAG architectures. Experience with on-device ML frameworks like Core ML, Foundation Model, etc. Experience in SwiftUI and modern iOS architectural patterns. Knowledge of model quantization, caching, and other on-device optimization techniques. Experience with multi-platform development (e.g., building for both iOS and macOS).

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