Senior Deep Learning Solution Architect, Cloud Computing Technologies Agile Development Labor Rate designs, develops, and implements state-of-art business software solutions that improves organizational operations through advanced applications and algorithms. Works with data scientists to create scalable cloud computing models that solve organizational problems. Capable of building deep learning systems (such as automated sales, marketing, research, accounting, data entry, and so on) that can learn how to respond without supervision from the data obtained from users and the guidance of their inherent algorithms. Interacts and works with end users to understand business problems and proffers and implements solutions to aid machine learning efficiency. Acquire, evaluate, and use historical data in defining and implementing the ways to automate and improve organizational operations. Collaborate with relevant departments – product design, accounting, research and so on – to develop efficient business models. May have Bachelor, Master, or Doctorate degree in computer science, information technology, computer engineering, mathematics, or any other related scientific fields or equivalent experience. Communication and data presentation skills and strong attention to details; self-motivated to achieve results in fast-paced and dynamic environment. Has creative mind love to solve complex problems. Senior Deep Learning Solution Architect must be proficient in computer programming languages such as Pythgon, Metlab, Java, R, or any other relevant programming language. Experienced in cloud computing technologies, hosting and deploying machine learning solutions, hiring and mentoring junior colleagues in the department, and machine learning statistical modelling. Possesses strong, evidential knowledge of deep learning and machine learning technologies such as MxNet, TensorFlow, Caffe, Torch, Theano, CNN, RNN, LSTM, and so on. Capable of implementing cutting edge solutions for large scale enterprise information technology systems in an organizational production environment. Capable of implementing deep learning, machine learning, and AI solutions that meet organizational needs.
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