As AI-based solutions expand to solve new and complex problems, the need for domain experts across disciplines to understand machine learning and apply their expertise in ML settings grows. This program invites experts in various fields to bring their unique domain knowledge to a team at Apple, and work collaboratively to create revolutionary machine learning and AI-powered products and experiences.
The program invests in the resident’s technical and theoretical machine learning development to help advance their professional careers. Residents have the opportunity to gain hands-on experience working on high-impact projects and develop new ML solutions that will impact future Apple products, learn from an Apple mentor, collaborate with fellow residents, publish in premier academic conferences, attend machine learning and AI courses, and partner with Apple teams across hardware, software, and services.
Please refer back to this page this fall to learn more about applying to the 2024 AI/ML Residency Program.
Related readings and updates.
Apple is proud to announce the 2021 recipients of the Apple Scholars in AI/ML PhD fellowship. Each Scholar receives two years of funding as they pursue their PhD, internship opportunities, and a two-year mentorship with an Apple researcher in their field. Nominated students were selected based on their innovative research, their record as thought leaders and collaborators in their fields, and their unique commitment to take risks and push the envelope in machine learning and AI.
Apple Scholars is a program created to recognize the contributions of emerging leaders in computer science and engineering at the graduate and postgraduate level. As part of Apple Scholars, Apple is proud to announce the recipients of PhD fellowships in AI/ML. In recognition of these outstanding PhD students, each will receive support for their research and academic travel for two years, internship opportunities, and a two-year mentorship with an Apple researcher in their field. Nominated students were selected based on their innovative research, record as thought leaders and collaborators in their fields, and unique commitment to take risks and push the envelope in machine learning and AI.