• Working knowledge of deep learning, machine learning and statistics.
• Experience in Deep learning using Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and LSTM
• Strong knowledge on deep learning applications with computer vision, image captioning, video analysis, image manipulation, image
segmentation, object detection and feature mapping.
• Functional expertise in DL modelling practices specific to data at hand (Size of model, training procedures, hand-designed layers etc.).
• Thorough understanding of state-of-the-art DL concepts (Sequence modelling, Attention, Convolution etc.) along with knack to imagine new
schemas that work for the given data.
• NLP expertise, especially in Language modelling, experience in using pre-trained language models (Transformer /GPT /BERT).
• Working Knowledge with GPU/CUDA programming
• Great programming skills with expertise in Python development standards.
• Fluency in Python package ecosystem especially ML/ DL packages like TensorFlow, Keras, PyTorch etc.
• Familiarity with code production standards and version control systems
• Excellent communication skills
· Master’s degree in Statistics, Applied Mathematics, or related discipline
· Professional certifications
· Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.