LR112 Senior Deep Learning Architect

Senior Deep Learning Architect, Cloud Computing Technologies Agile Development Labor Rate coordinates the architecting of scalable, multi-user micro-services back-end solutions. Possesses strong computer programming skills necessary for implementing highly-efficient deep learning and artificial intelligence solutions. Capable of using deep learning algorithms to test front-end and back-end codes. Ensures that all relevant coding guidelines are followed and avoids unnecessary complexities in building deep learning architectures. Able to use ML tools to simplify software development projects, including schedule management, cost estimation, project status tracking, quality control, security risk assessment, and human resources management. Possesses the ability to lead organization-wide architecture and development of deep learning solutions. Develop and implement deep learning algorithms into organizational systems at scale. Capable of handling big data and deep learning technologies in engineering large scale development systems. May have academic certifications or certifications in related fields such computer science, data science, data analytics, artificial intelligence, machine learning, deep learning, mathematics, and so on. May have up to 15 years of experience in different deep learning positions, including at 2 years of satisfactory experience in the implementation of deep learning or machine learning solutions and demonstrable expertise in deploying deep learning or machine learning models. Has solid knowledge of statistics, data science, data modeling, data analytics, probability theory, deep learning algorithms, software development, and so on. Has hands-on experience of using several programming, machine learning, deep learning, and big data technologies such as Python, Java, C++, Spring Boot, Kubernetes, Apache Spark, TensorFlow, Hadoop, Django, Docker, Computer vision, and so on. Thinks critically and creatively, questions assumptions and operational complexities, and resolves technical problems. Ensures that best practices are adhered to by its team members in the process of building deep learning architectures. Partners with relevant departments in accelerating customer adoption and revenue attainment through impeccable deep learning initiatives. Serve as the liaison between customer and artificial intelligence developers and product engineers in delivering customer-satisfying products.

Further rates within this Senior Deep Learning Architect category.