Applied Sensing Health, Embedded Systems Engineer

The Applied Sensing u0026 Health team develops software that powers the next generation of fitness, safety, and health experiences.

We transform complex, multi-modal sensor data from the iPhone, Apple Watch, and AirPods into meaningful and elegant insights about our users' health, wellbeing, and safety.

By combining advanced machine learning-including the integration and tuning of foundation models-with domain knowledge and scientific research, we have delivered impactful features like Cardio Fitness, Journaling Suggestions, Fall and Crash Detection, and Walking Steadiness.

As a dynamic and highly multi-disciplinary team working at the intersection of research and product development, you will have the opportunity to build the next generation of sensing-based features that will motivate, inform, and inspire millions of Apple's customers every single day.

You will help ship high-quality, interactive Health, Fitness, and Safety features that impact millions of Apple Watch, iPhone, and AirPods users.

You have a deep sense of ownership and feel a personal stake in the products you ship.

You are comfortable navigating ambiguity in early-stage development, demonstrate initiative, and work well under tight deadlines.

You build strong, collaborative relationships with others and are dedicated to a culture of continuous improvement for yourself, your team, and our products.

PhD in Computer Science, EECS, machine-learning or equivalent experience.

Strong background in developing deep learning, foundation, and/or generative AI models for multiple data modalities (time series, images, language, etc.) Experience collaborating with cross-functional teams and communicating technical concepts to non-technical stakeholders Excellent interpersonal skills and communication (written and verbal) Array