Job Details

Weekly Hours: 40

Role Number: 200622838-0836

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 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.

Minimum Qualifications

• Demonstrated expertise in deep learning with publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, COLM, ACL, NAACL, EMNLP, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, InterSpeech) or a track record in applying deep learning techniques to products

• 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.

• PhD, or equivalent practical experience, in Computer Science, or related technical field.

Preferred Qualifications

• Code Large language models.

• Reinforcement learning, on-policy distillation.

• Post-training, mid-training large language models.

• LM Context lengthening.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .