Machine Learning Engineer Apply
Our CompanyGentuity is an exciting and highly innovative medical technology firm, active in the research and development, clinical translation, and commercialization of vascular imaging devices. This opportunity provides the candidates the unique chance to work on innovative medical products, with the potential to significantly change the practice of medicine in the care of patients suffering from a wide range of highly debilitating vascular diseases.SUMMARY OF PRIMARY DUTIES AND RESPONSIBILITIES:Software and Algorithm DevelopmentResearch and development of research tools related to artificial intelligence, deep learning models, and signal/image processing algorithms.Evaluation of different deep learning models, algorithms, and training sets.Design and apply bioinformatics algorithms including machine learning and dynamic programming to medical imaging data sets.Create novel analytical tools as required by research goals.Develop new software applications or customize existing ones to meet specific scientific project needs.Develop data models, databases, and coordinate data annotation.Communicate Research ResultsCommunicate results through project reports.Consult with researchers to analyze problems, recommend technology-based solutions, or determine computational strategies.Confer with departments, such as marketing, business development, or operations, to coordinate product development or improvement.Participation in development of production quality software and other duties as assigned.EXPERIENCE/SKILL REQUIREMENTS:Must have:Tensorflow and/or PyTorch.PythonMachine Learning for Image or Data Processing (TensorFlow or similar packages)Experience in at least three of the following:Computer VisionMedical devices or imaging.Image Processing algorithmsAWS / Azure / Cloud solutionsPython, TensorFlow, PytorchGitExperience with building embedded software in medical, scientific, and/or analytical devices a plus.EDUCATIONAL REQUIREMENTS:Master’s degree or equivalent experience in a technical field (e.g., Computer science, Data Science, Electrical and Computer Engineering, Mathematics, or Physics)

