Deep Learning Engineer III, Cloud Computing Technologies Small Business Labor Rate is involved with the automation, enhancement, and maintenance of deep neural networks. Help with the building out and the expansion of technology platforms across a variety of software products. Responsible for setting up training pipelines to test and assess how well the deep neural networks or deep learning algorithms perform on relevant data processing platforms. Introduce the latest technologies and unique techniques into existing artificial intelligence technologies. Set up realistic synthetic training data for proper augmentation deep learning products. Involved in the development, tuning, testing, and deployment of deep learning systems to a wide variety of users. Carry out performance tests on existing frameworks to check for speed and accuracy, and make proper changes for improved efficiency. Have a Master’s degree or Ph.D. in Computer Science, Electrical Engineering, Statistics, or equivalent discipline. Have 11 or more years of experience training Deep Neural Networks, including CNNs, GRUs, and LSTMS. Demonstrate expertise in Software Engineering and Data Modeling fundamentals. Reliable with handling machine learning and boast of a reasonable level of familiarity with NLP and conversational systems. Have demonstratable hands-on experience and fluency with a variety of programming languages, with Python and Java at the top of the chart. Be an expert with the handling of SQL and other advanced analytical queries. Possess excellent understanding of advanced software design and DL model development. Experienced in the configuration and optimization of data pipelines used in developing deep learning algorithms that meet real life needs. Proficient knowledge of software programs such as TensorFlow, Keras, and PyTorch. Conversant with the development of linear, non-linear, and dynamic programming methods. Highly experienced with the diagnosis and debugging of errors with DL algorithms. Have problem-solving skills that drive the selection of approaches to solve specific issues. Have excellent communication skills to help get along with users and teammates. Keep up with previous and new in-depth research in deep learning and artificial intelligence academic articles and journals and other research publications to update knowledge. Work with the team under the supervision of the Senior Deep Learning Engineer.
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