Responsibilities : Experience with Machine Learning libraries, implementing and deploying ML-based offerings in production Leads definition of analytics vision, multiple use-case evaluations and selection criteria, as well as project-level scope definition Hands-on working experience in various AI powered model implementation with NLP Deep Learning Algorithms Expertise in platform development, distributed computing and micro services Strong Hands-on experience in Java/ Python programming skills and Web Services (spring boot) Experience implementing ML algorithms such as Logistic Regression, Naive Bayes, Bayesian Network, Decision Tree, Neural Network, SVM, Boosting, K-Means, Ensembler Classifiers, Random Forest, convex optimization, transfer learning. Development experience in the following technologies Kafka, Cassandra, MongoDB, Spark, Big Data Hands on experience with one or more Deep Learning frameworks such as Apache MXNet, TensorFlow, Caffe2, Keras, Torch and Theano Hands on experience on ML library
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