Machine Learning

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,