Overview
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!
Description 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. We are looking for engineers who are passionate about building systems that push the frontier of deep learning in terms of scaling, efficiency, and flexibility and delight millions of users in Apple products! Further, you will have opportunities to identify and develop novel applications of deep learning in Apple products. You will see your ideas not only published in papers, but also improve the experience of millions of users.
Responsibilities
* Contribute to building foundation models and related infrastructure, datasets, and tooling.
* Develop systems that scale, are efficient, and flexible to support Apple products and user experiences.
* Collaborate with engineers and scientists to tackle challenging problems in NLP, multi-modal understanding, and knowledge integration.
* Identify and develop novel applications of deep learning in Apple products and, where applicable, contribute to papers and publications.
Minimum Qualifications
* Proven track record in training or deployment of large models or building large-scale distributed systems.
* Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow.
* Ability to work in a collaborative environment.
Preferred Qualifications
* Web-scale information retrieval
* Human-like conversation agent
* Multi-modal perception for existing products and future hardware platforms
* On-device intelligence and learning with strong privacy protections
* PhD, or equivalent practical experience, in Computer Science, or related technical field.
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