MMongoScholar

Research Program

Apple Inc.

Apple Machine Learning Research Internship

United States · CaliforniaGraduatePhDPostdocProfessionalEntry ID: PR-08135

The Apple AIML Residency Program is a one-year research program designed for graduates with advanced degrees in STEM fields, emerging ML researchers, engineers, and interdisciplinary experts. Participants join Apple teams to work on high-impact machine learning and AI projects that influence future products and features. Residents collaborate with mentors, fellow residents, and cross-functional teams, gaining hands-on experience in solving complex real-world problems using ML-based solutions.

During the residency, participants attend Apple-led technical and leadership courses, pursue independent study, and have opportunities to publish findings at premier research venues. The program emphasizes interdisciplinary collaboration, fostering innovation in areas such as large language models, generative AI, computer vision, reinforcement learning, and more. Residents contribute to revolutionary AI-powered products while advancing their technical and theoretical ML skills.

This structured program supports career development for academics, engineers, and aspiring professors seeking industry experience in machine learning research. Specific roles, such as Siri Agent Modeling, focus on post-training multimodal LLMs, agentic intelligence, and prototype building for conferences.

Eligibility Requirements

  • 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
  • Graduate degree in a STEM field OR equivalent industry software engineering experience
  • Completed degree before program start (e.g., July 2026)
  • Strong programming skills (Python, C++, Swift, etc.)
  • Experience in ML areas like LLMs, Generative AI, NLP, CV, RL
  • Relevant capstone, thesis, internship, or industry work
  • Ability to collaborate in teams; full-time commitment

For thorough eligibility and selection information, visit the official website or contact the organizers directly.