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Bei uns erleben Sie Lernen und berufliche Weiterentwicklung in einer v\u00f6llig neuen Dimension.</p> <p><strong>Gesund leben, gesund arbeiten<br /></strong>Dar\u00fcber hinaus haben Sie Zugang zu Programmen wie unseren kontinuierlichen Lern- und Weiterentwicklungsprogrammen, der Erstattung von Studiengeb\u00fchren und Mentoring, um Ihr grenzenloses Potenzial auszusch\u00f6pfen \u2013 au\u00dferdem haben Sie die M\u00f6glichkeit, Ihre Lebensqualit\u00e4t durch unsere umfassenden, erstklassigen Leistungsangebote zu verbessern .</p> <p>Die Arbeit, die wir bei Qualcomm leisten, hat Auswirkungen auf das Leben rund um den Globus \u2013 und Sie k\u00f6nnen ein Teil davon sein. 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Must be available for 11 - 14 weeks during Summer 2025 (May-September) with a graduation date of December 2025 or later Proficiency in deep neural networks, machine learning algorithms, and architectures, including CNNs, RNNs, and LSTMs. Experience with deep learning and machine learning frameworks like TensorFlow, TFLite, PyTorch. Skills in neural network programming, video/image processing, and application development. Knowledge of compiler frameworks (LLVM, GCC, TVM, XLA) and parallel computing. Understanding of mathematical operations in linear algebra and fast math libraries. Theoretical knowledge of machine learning, deep learning, model compression, quantization, and optimization. Experience with reinforcement learning, neural architecture search, kernel optimization, and Bayesian optimization. Proficiency in on-device training, transfer learning, personalization, federated learning, NLP, and security and privacy in machine learning. Experience with deep generative models, audio/speech processing, NLP, computer vision, and wireless communication. Previous work on machine learning data pipelines, data management, and both backend and frontend applications. A track record of research excellence with high-quality publications in conferences like NeurIPS, CVPR, ICML, ICLR, and ICCV. Experience in object-oriented software design (OOSD). Candidates currently enrolled in a Master's or Ph.D. degree program in computer engineering, computer science, electrical engineering, or a related field. 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