deep learning scientist

Strong publication record (e.g., NIPS, ICML, CVPR, ICCV papers) and/or industry experience. Scientific expertise and real-world experience in deep learning (Recursive neural networks, Recurrent neural networks, convolutional neural networks, restricted Boltzmann machines, and deep neural networks) – applied to NLP. Experience in applying machine learning to problems in NLP. Natural language processing: sequence segmentation, labeling and parsing, knowledge extraction, question answering, multi text learning etc. Ability to come up with practical algorithms and write solid code quickly in a programming language (such as C++, Python, Scala, Java, GPU CUDA programming). Extensive experience with a neural network library such as Caffe, Keras, Tensorflow, or Torch. Rapidly prototype integration of latest research in the field into the product. Ability to work independently and be self-driven. Passion to work for Startup companies.


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