AIML - Machine Learning Researcher, Multimodal Foundation Models
20 days ago Zürich
About us
Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
- Size: 10,000+ employees
- Industry: Technology
Apple is where individual imaginations gather together, committing to the values that lead to great work. We are a group of engineers and researchers building multimodal foundation models at Apple, with a particular focus on image understanding and generation. We build infrastructure, datasets, and models with fundamental general capabilities and work with a cross-functional partners to apply these models to ship features to millions of users. 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.
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. 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, and also improve the experience of millions of users.
Preferred Qualifications
A track record in applying deep learning techniques to shipping products
Multi-modal perception for existing products and future hardware platforms
On-device intelligence and learning with strong privacy protections
Ability to quickly prototype ideas / solutions, perform critical analysis, and use creative approaches for solving complex problems.
Ability to collaborate closely with globally distributed teams.
Minimum Qualifications
Demonstrated expertise in deep learning with a publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL)
Deep understanding of multi-task, multi-modal machine learning domain
Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow
PhD, or equivalent practical experience, in Computer Science, or related technical field
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. 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, and also improve the experience of millions of users.
Preferred Qualifications
A track record in applying deep learning techniques to shipping products
Multi-modal perception for existing products and future hardware platforms
On-device intelligence and learning with strong privacy protections
Ability to quickly prototype ideas / solutions, perform critical analysis, and use creative approaches for solving complex problems.
Ability to collaborate closely with globally distributed teams.
Minimum Qualifications
Demonstrated expertise in deep learning with a publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL)
Deep understanding of multi-task, multi-modal machine learning domain
Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow
PhD, or equivalent practical experience, in Computer Science, or related technical field
Additional Information
- Posted: 20 days ago