Multi-modal human sensing is a foundational capability that powers intelligent experiences based on key human traits such as identity, expression, clothing, action, gesture, gaze and human-object interaction. As a Machine Learning Research Engineer on the SIML team, you will be responsible for designing and developing cutting-edge AI/ML models for human sensing, with a focus on building robust cross-domain identity recognition systems. Major Apple Intelligence experience such as personalized Natural Language Search, Memories Creation, as well as personalized Image Generation are powered by our ability to learn robust representations of visual human traits. Efficient real-time visual human sensing powers marquee Photography experiences, such as Cinematic Mode and Photographic Styles, and communication experiences such as Center Stage. This paves the way for more natural human-device interactions, for e.g., with the DockKit framework.Your primary responsibilities will include:* Designing, implementing, and deploying state-of-the-art visual recognition systems.* Directly interacting with all cross-functional stakeholders to gather product requirements and translating these into actionable plans for ML research and development. * Effectively communicating results and insights gained to partners and senior leaders, providing clear and actionable recommendations.* Staying abreast with the latest trends, technologies, and best practices in machine learning, multi-modal foundation models, computer vision and natural language understanding. * Actively contributing to ML community at the company by disseminating research ideas and results, enhancing shared infrastructure, and mentoring fellow practitioners.