AIML - Senior Applied Research Scientist, Health AI

Zurich, Zurich, Switzerland

Machine Learning and AI

The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit team of highly accomplished, deeply technical research scientists and machine learning engineers, focused on delivering innovative technologies that impact millions of users. We are looking for a research scientist passionate about solving real-world problems in the health domain that make a difference in our customers' lives.

Description

In this role, you will in part be a senior individual contributor and in part lead a small team focused on domain expertise with machine learning to impact health AI and health-related hardware design. You will use your leadership and IC skills to define metrics and goals and align with partners. You will also use your skills and experience in state-of-the-art machine learning and deep learning to design, implement and evaluate new machine learning models and algorithms to solve challenging problems involving unique data and objectives. You will have the opportunity to explore and develop hybrid scientific modeling and AI technologies and new areas within Apple to expand the team’s portfolio. The ability to substantially improve model performance from a prototype by using domain expertise of partners, novel architectures, optimizing hyper-parameters or exploring data augmentation techniques while staying aligned with partner roadmaps is key. Writing publications and being engaged with the academic community is desirable, but not necessary.

Minimum Qualifications

• Ph.D. in Computer Science, Machine Learning, or related fields, or an equivalent qualification obtained through alternative avenues.
• Extensive industry experience with a focus on applied machine learning.
• Hands-on expertise in pioneering machine learning and deep learning, incorporating domain knowledge such as Physics-informed ML and Sim2Real, applied to large-scale data and complex challenges.
• Strong background in generative models, constrained optimization, scientific models (optional), and statistical inference.

Key Qualifications

Preferred Qualifications

• Passionate about applying machine learning methods to enhance end-user experiences in the health sector.
• Proficient in developing large-scale models using modern machine learning frameworks such as TensorFlow, PyTorch, and Jax.
• Strong publication record in Machine Learning or AI, demonstrating the ability to contribute to groundbreaking research.
• Experienced in driving cross-functional collaborations across offices and time zones, with excellent interpersonal and communication skills, along with experience in mentoring and managing applied researchers.