Unknown Company

AIML Residency Program

northern, ky • Posted Yesterday
Remote Full Time Bio & Pharmacology & Health

Key facts

Location: Cupertino, CA Engagement: fellowship / residency

What you’ll do

  • You will join an Apple team to work on high-impact projects that directly influence future Apple products and features.
  • You will apply advanced science, technology, engineering, and mathematics (STEM) expertise to develop machine learning-based solutions for novel and complex challenges.
  • You will learn from an experienced Apple mentor who will guide your research and professional development throughout the fellowship.
  • You will collaborate with a cohort of fellow Residents to solve ambitious problems and share diverse perspectives.
  • You will publish your findings at premier research venues to contribute to the broader scientific community.
  • You will attend technical and leadership courses led by Apple and external educational institutions to refine your skill set.
  • You will pursue independent study to explore innovative ideas and push the boundaries of current machine learning research.
  • You will partner with research and development teams across Apple to ensure your work aligns with real-world product needs.
  • You will engage in a rigorous evaluation process that tracks your growth and impact on the projects you own.
  • You will help define the direction of machine learning applications that will shape the next generation of Apple technology.

Requirements

  • Eligibility for this fellowship is reserved for graduates with advanced degrees who are passionate about applying machine learning to complex problems.
  • You must possess expertise in various science, technology, engineering, and mathematics (STEM) fields or be an emerging ML researcher or engineer seeking to deepen your industry experience.
  • You must be authorized to work in the country where the position is located without requiring sponsorship now or at any time during the employment.
  • This role is not eligible for remote work or relocation assistance, reflecting the on-site nature of the residency in Cupertino, California.
  • You must be available to commit to a full-time, one-year program that demands active participation and collaboration.
  • You should be prepared to adhere to Apple’s policies regarding confidentiality and intellectual property.
  • You must be willing to engage in continuous learning through courses, mentorship, and independent study.
  • You must be legally authorized to accept employment in the United States and comply with all visa requirements for the duration of the program.

Nice to have

  • The program strongly prefers candidates who demonstrate a genuine interest in machine learning research and its practical applications.
  • Preferred candidates will have a track record of innovation and a desire to create revolutionary products rather than incremental improvements.
  • Experience in collaborating with cross-functional teams is highly valued, as the residency emphasizes interdisciplinary cooperation.
  • An interest in contributing to open academic communities through publications and conference participation is also preferred.

Practical notes

  • The Apple AIML Residency operates on a full-time schedule, requiring consistent in-person attendance in Cupertino, California, as this is an on-site fellowship.
  • The program does not offer remote work options, relocation assistance, or travel stipends for domestic or international relocation.
  • Compensation details are not specified in the available source material.
  • The application window for the 2026 cohort is currently open, and specific deadlines for submission are not provided in this overview.
  • Visa sponsorship is not available for this position, which means only candidates who already possess the necessary work authorization for the United States are eligible to apply.
  • The residency is designed to be a one-year commitment with a cohort of peers, focusing on long-term collaboration and deep research rather than short-term projects.

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