ML Research Engineer, HOUr - ISE

The Human and Object Understanding (HOUr) team in the Intelligent System Experience (ISE) organization at Apple is Looking for ML research engineers in the space of advanced face understanding and analysis. This is an opportunity to join a team that built the enabling ML technologies behind a number of marquee products and features such as:

Visual User Identification stack for Apple HomeView.
Visual Age Estimation for Child Safety on Apple Platforms.
Gaze understanding in Camera & Photos, Accessibility.
Liveness assessment for IDs in Apple Wallet, and more.

You must have a proven track record of domain expertise and technical leadership in applied ML research.
You will partner closely with feature and product teams across the company to build use-case specific and feature enabling technologies in areas such as understanding visual identity, facial attributes, face liveness and anti-spoofing, eye tracking and gaze analysis.
You will leverage state-of-the-art techniques to develop highly efficient, real-time solutions where needed, and/or also leverage pre-trained large scale visual/multimodal foundation models to achieve state-of-the-art quality for specific downstream use-cases.
You will be interacting very closely with a variety of ML leaders, researchers, software engineers, hardware & design teams cross-functionally in order to build and ship new experiences based on your technologies.
Ensuring quality in the field, with an emphasis on fairness and model robustness would constitute an important part of the role.

Minimum Qualifications

Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience.
Extensive knowledge and experience in leveraging large scale foundation models including multi-modal LLMs or vision-language models, including adapting/distilling pre-trained models for downstream perception tasks.
Strong programing skills in Python and proficiency in toolkits like Pytorch or equivalent deep learning frameworks.
Proficiency in leveraging AI coding and productivity tools, to supercharge experimentation and model training iterations.

Preferred Qualifications

Strong background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful industry experience.
Experience in addressing challenges associated with the transition of a prototype into a shipping product.
Familiarity with challenges of developing algorithms that run efficiently on resource-constrained platforms.
Excellent written and verbal communication skills, be comfortable presenting research to large audiences, and have the ability to work in multi-functional teams.