AIML - Machine Learning Engineer, Foundation Models
Job Description
Summary
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 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.
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.
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.
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.
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.
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
