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Experience: 3+ Years

Job Location: INDORE, BANGALORE/Bengaluru


  • Machine Learning, Deep Learning, Python/R, Keras, Tensorflow, OpenCV, Regression, Clustering, AWS.
  • Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modelling, Logit/Probit Model, Affinity & Association, Time Series, DoE, distribution / probability theory.
  • (Deep Learning) - ANN, CNN, RNN, LSTM, Bi-LSTM, GRU, RCNN.


  • Fundamental understanding of mathematical techniques involved in ML and DL schemas (Instance-based methods, Boosting methods, PGM, Neural Networks etc.)
  • Thorough understanding of state-of-the-art DL concepts (Sequence modeling, Attention, Convolution etc.) along with knack to imagine new schemas that work for the given data.
  • Fluency in Python package ecosystem especially ML/ DL packages like TensorFlow, PyTorch etc.
  • Solid experience and proven track record with developing & deploying deep learning algorithms including CNNs [VGG16, ResNet, DenseNet], RNNs, LSTM, Autoencoders, Generative adversarial network, Siamese network and others.
  • NLP expertise, especially in Language modelling, at-least experience in using pre-trained language models (Transformer /GPT /BERT)
  • Design and develop software modules that perform data ingest, data transform, and analytics tasks
  • Exposure in both the theory and practice of machine learning techniques (supervised and unsupervised learning, Computer Vision, Image Processing, Natural language processing etc.)
  • Applied experience with Deep Learning architectures such as Convolutional Neural Networks [VGG16, ResNet, DenseNet], Autoencoders, Generative adversarial network, and Siamese network.
  • Application of object detection and localization models like YOLO, RCNN, Mask-RCNN etc.
  • Good understanding of OpenCV
  • Should have skills for applying automation of the processes, and designing A.I. pipelines


  • Experience working with neural nets (way beyond MNIST classification please).
  • Great grasp of how deep learning works and experience with either Caffe or Tensorflow
  • Real example of models you have built and trained. No tutorials please.


  • Natural Language Processing (NLP)
  • Object detection, Recognition
  • Facial detection & Recognition
  • Automatic image segmentation


  • Having an experience on Bathymetry.
  • Already deployed deep learning solutions (focused on computer vision) in production.Kindly forward this mail to your contacts who might be interested in this job role.

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