Job Abstract

Are you excited about the ways Machine Learning can make all Apple products more intelligent and personalized? From extending your battery life, to accelerating app launches, to preserving your battery health, the OS Intelligence team builds innovative ML solutions ranging from predictive forecasting models to deep foundation models that improve the user experience originating from the core of the operating system. Within the umbrella of Core OS Power & Performance, the Energy Technologies division focuses on solving key resource tradeoff and optimization problems, which sets Apple products apart. The OS Intelligence team within this group is a focused Applied Machine Learning team that imbues the low layers of the operating system with Machine Learning-based intelligence and ships key features and technologies in every year’s OS releases.The team is looking for extraordinary candidates to design Deep Learning architectures, implement industry-leading Machine Learning algorithms, as well as contribute high-quality software to iOS, iPadOS, macOS, watchOS, visionOS, and more. In this unique and highly visible role, you will be working cross-functionally to add intelligence to new domains to create beautiful user experiences. Through data analysis, ML model development, and on-device software development, you will push the boundary of what's possible in an operating system.

In this role, you will have the opportunity to:-Innovate, conceptualize, and prototype novel intelligent experiences by leveraging recent advances in LLMs, sequence-to-sequence models, and fine-tuning (like LoRA adapters, RAG pipelines) to architect foundation models for a diverse set of applications in the OS.-Build scalable cloud-based and on-device infrastructure to accelerate seamlessly running experiments and monitoring shipped models.-Analyze, understand, and present key performance data for highly-visible OS features.-Write elegant, performant code in Objective-C or Swift and test, debug, and productize it.-Consult with and influence other teams to drive adoption of new APIs.