AIML - ML Researcher, Foundation Models
il y a 2 jours
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
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.
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 our products. You will see your ideas not only published in papers, but also improve the experience of millions of users.
Preferred Qualifications
PhD, or equivalent practical experience, in Computer Science, or related technical fields.
High performance parallel and distributed computing.
Minimum Qualifications
Constantly seeking challenging problems to work on and new area to learn from.
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.
At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.
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