The Health Personalization team builds outstanding technologies to support AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing, and support them to achieve their health and wellness goals. As part of the larger Sensor Software & Prototyping team, we take a multimodal approach using a variety of sensors and user data signals across hardware platforms, such as camera, wearables, and natural language user 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

We are looking for an applied scientist with deep expertise in health applications of machine learning, from the details of challenging health data modalities to the nuances of meaningful evaluation for health interventions. In this role, you will be at the forefront of developing, evaluating, and improving generative models for real-world health and wellbeing applications. You’ll have the opportunity to work in a fast-growing team of highly skilled scientists and engineers to develop generative systems that achieve the highest levels of quality, reliability, and alignment with human intent.

MINIMUM QUALIFICATIONS

• MS or PhD in a detailed quantitative field such as computer science, mathematics, statistics, economics, health informatics, or similar, and 5+ years of relevant proven experience
• Technical expertise and hands-on experience crafting and evaluating machine learning solutions for applications in health
• Experience applying a scientific approach to drive machine learning innovation: developing hypotheses, designing experimentation strategies, and guiding data generation / collection (e.g. user studies, annotation workflows, A/B tests).
• Proficiency using python and deep learning frameworks (e.g. PyTorch) in a peer-reviewed environment
• Knowledge of health informatics or experience with complex health data sources (e.g. EHRs, medical ontologies, wearables)

PREFERRED QUALIFICATIONS

• Technical expertise in generative AI domains, such as large language model architectures, memory representation, planning, knowledge retrieval, natural language understanding
• Hands-on experience developing complex generative AI systems in an applied setting, eg experience with post-training techniques like supervised fine-tuning, adapter training, and reinforcement learning from human feedback.
• Familiarity with privacy-preserving ML techniques
• Strong communication skills, comfort working with multiple engineering teams on complex projects, and experience contributing to an inclusive team culture

Please refer the Job description for details