Manager, Machine Learning Research SIML, ISE

The Human and Object Understanding (HOUr) team at Apple is looking for ML leaders in the space of advanced face analysis. This is an opportunity to join a team that built the fundamental ML technologies behind a number of marquee features spanning Camera Photos Accessibility Apple Wallet Apple Intelligence and are looking for world class technology leaders that have the ability to translate ideas to action and lead a team of experts to innovate build deploy and maintain groundbreaking face understanding and perception technologies to enable a variety of new features across the Apple ecosystem such as:nn- User gaze from RGB images to enable novel interaction experiences: nn- Face liveness in the RGB domain for anti-spoofing user authentication and security: nn- Face analysis for creating exciting new Camera and Photos experiences: nn- Rich face attribute understanding for enabling personalized and identity preserving image generation and much more! nnWe are seeking a leader to join our team who can thrive in cross-functional settings can provide critical technical expertise and leadership and be responsible for delivering ML solutions that serve the intended experiences while respecting practical constraints such as memory latency and power.

Candidates for this role must have a proven track record of leadership in applied ML research. The primary responsibilities associated with this position include providing mentorship and technical guidance to a team of ML experts guiding the team to transform research into impactful solutions in production via extensive multi-functional collaboration staying abreast with academic and industry advancements and best practices in ML. You will be leading an ML team to build the next generation of face analysis technologies such as understanding facial attributes face liveness and anti-spoofing eye tracking and gaze analysis. nnYou will lead the charge in leveraging 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 innovative quality. You will be interacting very closely with a variety of ML leaders researchers software engineers hardware u0026 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 PRIMARY RESPONSIBILITIES WILL INCLUDE:nLeading an ML team in designing implementing and deploying state-of-the-art solutions for advanced face analysis and interacting with all cross-functional stakeholders to gather product requirements and translating these into actionable plans for ML research and development. nnEffectively communicating results and insights gained to partners and senior leaders providing clear and actionable abreast with the latest trends technologies and standard methodologies in computer vision machine learning and large scale foundation models. nnActively contributing to ML community at the company by disseminating research ideas and results enhancing shared infrastructure and mentoring fellow practitioners.

Masters or Ph.D. in Computer Science or Computer Engineering; similarly related fields or comparable professional technical leadership in industry and experience in leading ML teams focused on productizing knowledge and experience with large scale foundation models including multi-modal LLMs or vision-language models including pre-training and/or adapting pre-trained models for downstream perception to be hands-on when needed: Strong programming skills in Python and C and proficiency in toolkits like Pytorch or equivalent deep learning frameworks.

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