Senior Engineer - Health AIML

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 passionate about delivering innovative technologies that benefit our users. We are seeking a mission-driven, hands-on technical leader to spearhead new strategic initiatives at the intersection of health and artificial intelligence.

Description

In this role, you will leverage your deep technical expertise to push beyond state-of-the-art methodologies. You will be responsible for guiding the full lifecycle of applied research-from concept to production-by applying novel AI/ML techniques to unique challenges in the health space. You will partner closely with product, design, and other research and engineering teams to translate cutting-edge research into the next generation of Apple health products, all while upholding the privacy standards for which Apple is known. As a leader, you will be responsible for mentoring a world-class engineering organization, fostering a culture of continuous improvement, and cultivating collaboration with peers across AIML and Apple.

Minimum Qualifications

10+ years of experience in a technical leadership role, with a demonstrated history of shipping complex AIML products.

Experience with systems engineering; in-depth understanding of interdependencies of ML and SW components.

Demonstrated ability to form senior partnerships and influence technical direction across a large, cross-functional organization.

Strong intuition for turning ambiguous research questions into concrete technical roadmaps and product opportunities.

Expertise in generative AI technology and large language models (LLMs) is highly desirable.

MS/PhD in Machine Learning, Computer Science, or equivalent experience in a related field.

Preferred Qualifications

Extensive experience delivering large-scale product or platform outcomes, leveraging cross-functional partnerships.

Proven record of gaining technical expertise on the job; demonstrates the ability to learn new technologies independently.

Excellent understanding of an ML-based product lifecycle.

Demonstrated depth of knowledge and application of statistics-based evaluation methodologies or user success metrics.

Expertise in generative AI technology, large language models (LLMs).

Experience with systems engineering; in-depth understanding of interdependencies of ML and SW components.

Proven innovation record.

Experience providing technical guidance to an engineering organization.

Ability to develop a long-term vision and execute strategies at scale while maintaining a grasp of technical details for better decision-making.

Experience in establishing and maintaining technical cross-functional partnerships across multiple organizations.

Experience with technical presentations for multiple audiences, including executives.