AIML - Applied ML Research Scientist, Accessibility

We are seeking an Applied Machine Learning Research Scientist to join our Accessibility efforts on the Human-Centered Machine Intelligence (HCMI) team within AIML at Apple. Research Scientists in HCMI tackle significant technical and human-centered research challenges, collaborate with partner teams across Apple to ship products, and shape the field of human-centered AIML via external publication and engagement. Join us to design, study, and build intelligent interactive technologies that enable people of all abilities to use Apple technology.

Description

The Human Centered Machine Intelligence (HCMI) group designs, studies, and builds interactive technologies that enable people to benefit from machine learning. We are a close-knit team of research scientists and engineers in a unique position to do research and work closely with product teams throughout Apple. Our work has resulted in numerous award-winning research publications and groundbreaking technologies impacting millions of people. The Accessibility team within HCMI specifically focuses on core ML technologies that address grand challenges in accessibility, including equitable speech access to people with disabilities, visual understanding for people who are blind or low vision, communication access for people who use sign language, and more.

Minimum Qualifications

PhD in Machine Learning, Human Computer Interaction, Computer Science, or related field.
Experienced researcher in areas of machine learning, including computer vision or multi-modal modeling.
Publication and research record commensurate with seniority.
Proven history of turning research contributions into tools, guidelines, or products either commercially or as open source, or strong potential to do so.

Preferred Qualifications

Experience designing machine learning models for sign language.
Experience conducting research in Accessibility (e.g., sign language, atypical speech, visual accessibility, or other topics).
Experience doing data collection or data curation (e.g., developing data or annotation protocols).
Experience with human-centered evaluation methods (e.g., developing user study protocols or running studies).
Experience developing and shipping products that use machine learning.
Strong writing and presentation skills.