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Position: Sr. Machine Learning Engineer, Data & Machine Learning Innovation
Institution: Apple Inc.
Location: Cupertino, California, United States
Duties: Improving current products and future hardware platforms with ML 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; Developing on-device intelligence and learning with strong privacy protections; 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
Requirements: Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics, related field; or equivalent experience; 5+ years of demonstrated experience with developing and evaluating ML applications, and in understanding and improving data quality; Expertise in natural language processing, search and recommendation, and machine learning with a passion for data-centric machine learning
   
Text: Sr. Machine Learning Engineer, Data & Machine Learning Innovation Improving current products and future hardware platforms with ML 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; Developing on-device intelligence and learning with strong privacy protections; 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 Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics, related field; or equivalent experience; 5+ years of demonstrated experience with developing and evaluating ML applications, and in understanding and improving data quality; Expertise in natural language processing, search and recommendation, and machine learning with a passion for data-centric machine learning
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