Update - As of January 2024, applications for the 2024 Residency Program are closed.
The Apple AIML Residency is a one-year program for graduates with advanced degrees, designed to spur interdisciplinary collaboration and apply it to ML-based solutions to solve new complex problems. The program supports experts in various science, technology, engineering, and mathematics (STEM) fields, as well as emerging ML researchers and engineers as they work collaboratively to create revolutionary machine learning and AI-powered products and experiences.
Our program welcomes a range of candidates including:
- Master’s degree graduates
- Recent PhD graduates and postdocs
- Software and hardware engineers interested in collaborating with research or ML teams
- Academics seeking a sabbatical to focus on work or research in the ML industry
- Aspiring professors seeking industry experience
Residents will gain hands-on experience as they join an AIML team for one year and work on high-impact projects that impact future Apple products and features. Residents will learn from an Apple mentor, collaborate with fellow Residents, publish at premier research venues, attend Apple-led and external technical and leadership courses, pursue independent study, and partner with research and development teams across Apple.
Related readings and updates.
The 2025 AIML Residency Program Application is Now Open
Introducing Apple Scholars in AIML
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 AIML. 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.