Deep Learning Internship (6 Months)

You will be responsible for building deep learning models using TensorFlow/PyTorch. Collaborate with the team to ensure proper testing and deployment of the models. Demonstrate good knowledge and understanding of Deep Learning Algorithms in both NLP (LSTMs, RNNs, etc.) and Computer Vision (CNNs, etc.) domain, as well as TensorFlow and deep learning frameworks like Keras, PyTorch to solve real-life problems. Create and update documentation for the work done. Understand deep learning algorithms implementation from scratch such as LSTM, RNNs, DNNs, BI-LSTMs. Work on Computer Vision and Image processing, as well as TRANSFER LEARNING - GANs. Minimum qualifications include a Master or PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience. Relevant internship or work experience with data analysis. Experience with statistical software (R, Python, S-Plus, SAS, or similar) and database languages (e.g. SQL) is required. Preferred qualifications include a Master's or B.Tech in relevant field. Your responsibilities will include researching on given machine learning/data science topics for writing articles for company websites. Assist with hands-on coding on Jupyter Notebook for providing code snippets in the articles. Work on short projects & assignments, deployment techniques, and design and implement machine learning, information extraction, probabilistic matching algorithms and models. Use your passion for programming and deep learning/AI skills using Python, TensorFlow, and deep learning frameworks like Keras, PyTorch to solve real-life problems. Develop AI solutions in the computer vision domain using convolutional neural networks (CNN) and a combination of deep neural networks such as CNN & RNN. Solve object detection, recognition, image classification problems using machine learning and deep learning algorithms & transfer learning methods and techniques. Use innovative & automated approaches for data annotation, labeling, and data augmentation & use active learning. Handle online code assistance, code mentoring, and education-based solutions. Perks include Certificate, Letter of recommendation, Flexible work hours, Informal dress code, 5 days a week, Free snacks & beverages.,