Applied AI Engineer - Health

The Health Personalization team builds AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing. We harness large language models and the latest ML advances to build products that are useful, personal, privacy-preserving, and safe - turning research and incubation into features people rely on every day. As part of the larger Sensor Software & Prototyping team, we work across hardware platforms and data modalities including wearables and natural language input. We are committed to building deeply personal features that understand, anticipate, and adapt to users behaviors and uphold Apples deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us! In this role, you will prototype, develop, evaluate, and ship Generative AI experiences for real-world health and wellbeing applications. Youll apply strong ML fundamentals, build practical evaluation methods, and ground your work in real on-device user interactions. Your work will directly shape customer-facing health products across the full ML lifecycle.

A strong candidate makes progress through ambiguity - building, learning from real data, and iterating toward the right answer rather than waiting for the perfect plan. They take ownership of outcomes end-to-end, prioritize well, and learn fast.Develop and improve generative AI systems for health and wellbeing applications across the full feature development lifecycle - prototyping on-device experiences to explore design directions, and shipping production-quality features. Independently design, run, and analyze ML experiments to deliver measurable quality improvements. Design and implement evaluation frameworks - including automated assessment tools, LLM-based autograders, and benchmarks - to measure and improve model quality. Analyze algorithm and feature behavior, identify failure modes, and drive actionable improvements through experimentation and failure analysis - verifying that fixes hold with data. Work cross-functionally with many teams - including clinical experts, designers, and HW and SW teams, and more - to bring features into production with real-world applicability and impact.BS and a minimum of 3 years relevant industry experience Ability to leverage AI-assisted tooling to write clean, performant code (e.g. Python), while maintaining full ownership of code quality and software development best practices (e.g. Git). Technical expertise and hands-on experience building and evaluating machine learning solutions for user-facing applications. Comfort building functional prototypes or proof-of-concept demos to test ideas quickly.MS or PhD in computer science, machine learning, health informatics, biomedical engineering, or a related quantitative field - or equivalent industry experience. Strong communication skills and ability to work cross-functionally with technical and non-technical stakeholders. Technical expertise in generative AI domains, such as large language model architectures, knowledge retrieval, and natural language understanding. Deep expertise with LLM-based evaluation systems and evidence-based approaches to test development and quality measurement. Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products. Experience building and deploying performant on-device or full-stack systems, including rapid prototyping of user-facing experiences (e.g. Swift, SwiftUI), is a plus.