Design, implement and evaluate models, and build software prototypes of machine learning systems related to Computer Vision, Deep Reinforcement Learning, NLP, ASR, Audio Processing.
Help lay the technical foundation of new businesses, products and services, and leverage ML to increase the operational efficiency and help in massively-scalable distributed compute product architectures
We have deep learning expertise and its application in Neural Network architectures to Computer Vision, Natural Language Processing, Machine Intelligence and Reinforcement Learning
Expertise in deep learning frameworks such as Pytorch, Torch, Caffe, Tensorflow.
We have strong publication record in highly ranked ML and AI conferences and journal publications.
Expertise in Computational Neuroscience modeling experiences
One or more programming languages: C++/C, Python, Java, MATLAB, OpenCV,
Experience with microservices oriented architectures, TensorFlow based AI orchestration, test driven development (TDD) & other testing methodologies, and a zeal for automation at all level
Experience with scaling Big Data infrastructure (HDFS, Solr, ELK, Spark)
Design and implement the core NLG engine to Narrative Science's Advanced Natural Language Generation Platform, drawing concepts from generative syntax.
Design and implement the NLP/NLU engine for conversational interface to the platform based on principles from compositional semantics - with R, WEKA, RASA
Experience in conversational AI, democratized AI.
Expertise in: Sentiment Analysis, Entity Extraction, Document Classification, Topic Modelling, Natural Language Understanding (NLU), or Natural Language Generation (NLG) , text pre-processing and normalization techniques, such as tokenization, POS tagging and parsing and how they work at a low level.
Experience with classification, feature engineering, information extraction, structured prediction, clustering, semi-supervised learning, topic modelling, and ranking
Expertise in linguistics and language as a phenomenon.