ML-AI

SKILLS:

• 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.

JOB DESCRIPTION:

• 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

MUST HAVE

• 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.

EXPERTISE IN ANY ONE OF THE BELOW AREAS:

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

GOOD TO HAVE

• 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.