LR081 Deep Learning Engineer II

Deep Learning Engineer II, Cloud Computing Technologies Agile Development Labor Rate is responsible for developing and validating several deep neural network architectures to extract knowledge and information from data collected through deep learning algorithms. Develop state-of-the-art deep neural networks for the processing of aerospace multispectral images. Create and design machine learning algorithms on a variety of software programs such as Keras, TensorFlow. Deploy created algorithms on several hardware programs. Work in collaboration with application developers and other engineers to facilitate the creation of new models, systems, and tools that enables the building of the best kinds of deep neural networks. Part of a passion-driven team to design and train state of the art deep learning algorithms. Manage and curate various datasets to plan and write functional specifications for a variety of deep learning algorithms while prioritizing correctly. Have a Master’s degree or Ph.D. in Computer Science, Electrical Engineering, Statistics, or equivalent discipline. Have 6-10 years of experience training Deep Neural Networks, including CNNs, GRUs, and LSTMS. Demonstrate expertise in Software Engineering and Data Modeling fundamentals. Be reliable with handling machine learning and boast of a reasonable level of familiarity with NLP and conversational systems. Have significant hands-on experiences and fluency with a variety of programming languages with Python at the top of the chart. Expert at handling SQL and other advanced analytical queries used for database programming. Possess excellent understanding of general software design patterns and DL models leveraging reinforcement learning. Experienced with the configuration and optimization of data pipelines. Proficient knowledge of software programs such as TensorFlow, Keras, and PyTorch. Conversant with the development of linear, non-linear, and dynamic programming. Be highly experienced with the diagnosis and debugging of errors with ML algorithms. Have problem-solving skills that drive the selection of approaches to solve specific issues. Ready to take on new initiatives to improve deep learning capacities in a rapidly scaling environment. Work under the supervision of the Senior Deep Learning Engineer.

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