About The Position

We are a group of engineers and researchers responsible for building foundation models at Apple. We build infrastructure, datasets, and models with fundamental general capabilities such as understanding and generation of text, images, speech, videos, and other modalities and apply these models to Apple products. We are looking for researchers who are passionate about developing algorithms, techniques, and systems that push the frontier of deep learning and delight millions of users with Apple products powered by foundation models. We believe that the most interesting problems in deep learning research arise when we try to apply learning to real-world use cases, and this is also where the most important breakthroughs come from. You will work with a close-knit and fast-growing team of world-class engineers and scientists to tackle some of the most challenging problems in foundation models and deep learning, including natural language processing, multi-modal understanding, and combining learning with knowledge.

Requirements

  • Strong background in deep learning and machine learning.
  • Experience with natural language processing and multi-modal understanding.
  • Ability to develop algorithms and techniques for real-world applications.
  • Proven track record of research and publications in relevant fields.

Nice To Haves

  • Experience with large-scale data processing.
  • Familiarity with privacy-preserving machine learning techniques.
  • Knowledge of Apple products and ecosystem.

Responsibilities

  • Identify and develop novel applications of deep learning in Apple products.
  • Work on web-scale information retrieval.
  • Develop human-like conversation agents.
  • Enhance multi-modal perception for existing products and future hardware platforms.
  • Implement on-device intelligence and learning with strong privacy protections.
  • Collaborate in a team environment.

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What This Job Offers

Industry

Computer and Electronic Product Manufacturing

Number of Employees

5,001-10,000 employees

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