As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in foundation models to tackle complex data problems. The solutions you develop will significantly impact future Apple products and the broader ML development ecosystem.You will work with a multidisciplinary team to actively participate in the data-model co-design and co-development practice. Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for foundation models at Apple. You will also be responsible to create robust model evaluation pipelines, integral to the continuous improvement and assessment of foundation models. Additionally, your role will entail an in-depth analysis of multi-modal data to underscore its influence on model performance.Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.Your work may span a variety of applications, including but not limited to:- Enhancing current products and future hardware platforms with multi-modal perception data- Designing and implementing semi-supervised, self-supervised representation learning techniques for maximizing the power of both limited labeled data and large-scale unlabeled data.- Employing data selection techniques such as novelty detection, active learning, and core-set selection for diverse data types like images, 3D models, natural language, and audio.- Uncovering patterns in data, setting performance targets, and leveraging modern statistical and ML-based methods to model data distributions. This will aid in reducing redundancy and addressing out-of-distribution samples.