We have an opening for an image-based, deep learning research scientist with strong academic foundations, and substantial hands-on experience with image-based convolutional networks, to join our core startup team of computer vision scientists.
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
· Image processing & 2D/3D computer vision foundations
· Strong Python software development skills
· C++ software development skills in Linux environments
· Familiarity with machine learning modeling frameworks (TensorFlow, Theano, Caffe, Torch)
· Excited about seed-stage startups; entrepreneurial, comfortable with risk & uncertainty
· GPU parallel processing experience desired
· U.S. work visa required
· Rare opportunity to join an early tech startup adventure when it is less than ten people, led by founders who’ve taken two startup teams through IPO.
· Substantial stock equity packages, of the sort only available to early startup employees.
· Opportunity to publish novel and influential research, participate in scientific conferences, and collaborate with partners in academia.
· We are located in Mountain View, California, but we have technical staff located around the globe. We prefer local candidates, but are open to remote work/telecommuting or part-time consulting for the right candidate.