Job Description

The Machine Intelligence, Neural Design (MIND) team is leading Apple-wide innovation on HW/SW co-design for efficient inference. We are seeking a highly motivated, results-driven team player with a strong background in machine learning and systems, along with hands-on software development experience. The role focuses on optimizing mobile-cloud hybrid inference for multi-modal large language models (LLMs), with emphasis on both systems-level innovation and ML co-design.



Our mission is to advance the state-of-art in ML optimization techniques for efficient inference. Thus, the ideal candidate for this position is a researcher and engineer who will relentlessly push the existing boundary with out-of-box thinking, and materialize the idea with the very details to impact both Apple partners and research communities.

Description

Research and develop ML optimization techniques for efficient on-device ML


Materialize the ideas/concepts and demonstrate the practical value in an industrial environment


Work with HW/SW teams to productize the outcome of the work

Preferred Qualifications

Experience with Large-scale model training/tuning



Experience with processing multiple modalities (i.e., audio/vision) with Foundational Models.



Experience with backend compilation, HW/SW co-design, and/or performance optimization



Understanding ML accelerations and architectures

Minimum Qualifications

Expert in Python/PyTorch programming



Quality publications in System optimization (e.g., MICRO, ASPOLOS, OSDI, NSDI, MobiSys etc).



Quality publications in ML optimization (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, etc).



Excellent communication and writing skills



Ph.D. in CS/CE or related fields



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 .