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Position: Deep Learning Vision Scientist
Institution: MoTek Technologies
Location: San Francisco, California, United States
Duties: As a Deep Learning Scientist, you will design high-performance, state-of-the-art, hybrid architectures for image-based classification, segmentation, labeling, and object detection. This position requires strong theoretical foundations, excellent engineering skills, and sound scientific method. Candidates must have broad and deep proficiency in the foundations of machine learning, CNNs, image processing and computer vision. Candidates must also be adventurous and enthusiastic about an early startup experience!
Requirements: Strong academic foundations from a competitive university/laboratory (Ph.D. preferred); Fluent with state-of-the-art techniques for image-based machine learning; Substantial experience architecting, training, optimizing and evaluating image-based ConvNets; Practical experience building pixel-based image segmentation/boundary/classification networks; Strong applied math skills in linear algebra and linear & non-linear optimization; Solid scientific method & excellent data analysis skills
   
Text: Deep Learning Vision Scientist As a Deep Learning Scientist, you will design high-performance, state-of-the-art, hybrid architectures for image-based classification, segmentation, labeling, and object detection. This position requires strong theoretical foundations, excellent engineering skills, and sound scientific method. Candidates must have broad and deep proficiency in the foundations of machine learning, CNNs, image processing and computer vision. Candidates must also be adventurous and enthusiastic about an early startup experience! Strong academic foundations from a competitive university/laboratory (Ph.D. preferred); Fluent with state-of-the-art techniques for image-based machine learning; Substantial experience architecting, training, optimizing and evaluating image-based ConvNets; Practical experience building pixel-based image segmentation/boundary/classification networks; Strong applied math skills in linear algebra and linear & non-linear optimization; Solid scientific method & excellent data analysis skills
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