LR111 Deep Learning Architect III

$117.15

Deep Learning Architect III, Cloud Computing Technologies Agile Development Labor Rate assesses deep learning architectures, including deep learning algorithms and applications. Responsible for selecting the hardware on which deep learning model can run with the best latency. Builds algorithms that help programmers detect errors in software codes and analyze errors in models with ease to avoid post deployment security challenges or application malfunction.

SKU: LR111 Categories: , ,

Deep Learning Architect III, Cloud Computing Technologies Agile Development Labor Rate assesses deep learning architectures, including deep learning algorithms and applications. Have proven track records of implementing deep learning solutions through the use of multiple programming languages. Capable of developing deep learning driven features for organizational systems and devices. Capable of detecting errors in deep learning coding that can affect both the functional and non-functional requirements of the end product. Builds state-of-the-art artificial intelligence/machine learning/deep learning tools that solves complex problems of customers and clients. Develops deep learning algorithms that run supply chains, customer fulfillment paths, sales forecasting, and capacity planning for e-commerce and other services organizations. Experienced in using deep learning/machine learning tools and technologies such as PyTorch, Apache, MxNet, SageMaker, TensorFlow, Keras; and multiple programming languages such as Python, LISP, Perl, and so on. May have certifications in technical fields such as computer engineering, data science, big data technologies, databases, software development, artificial intelligence, statistics, technical architecture, probability theory, and so on. In collaboration with the Senior Deep Learning Architect, develops strategies for ensuring data acquisition, data quality, data validation, data cleaning, and data augmentation. Builds algorithms that help programmers detect errors in software codes and analyze errors in models with ease to avoid post deployment security challenges or application malfunction. Responsible for selecting the hardware on which deep learning model can run with the best latency. Partners with customer experience, product research, and data scientists to understand their business and technical needs and implement artificial intelligence (AI) solutions that meet current requirements and is able to evolve over time in meeting future requirements. Experienced in architecting artificial intelligence and deep learning applications and using full-stack applications such as Microsoft Azure. Possess excellent analytical, creative, problem-solving, innovative, project management, and communication skills.

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Cloud Computing Technologies

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