Applied AI Engineer - Health
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 30, 2026. Apple scores A on the Alion truth index.
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 Apple's deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us!
Description
In this role, you will prototype, develop, evaluate, and ship Generative AI experiences for real-world health and wellbeing applications. You'll 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.
Minimum Qualifications
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.
Preferred Qualifications
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.