Deep Learning Internship (6 Months)

As a Deep Learning Engineer, your role involves building deep learning models using TensorFlow/PyTorch. You will collaborate with the team to ensure proper testing and deployment of these models. Your responsibilities include having a good understanding of Deep Learning Algorithms in NLP and Computer Vision domains, such as LSTMs, RNNs, CNNs, etc., and using TensorFlow and frameworks like Keras, PyTorch to solve real-life problems. Additionally, you will be creating and updating documentation for the work done and implementing deep learning algorithms from scratch, including LSTM, RNNS, DNNS, BI-LSTMS. You will also work on Computer Vision, Image processing, and TRANSFER LEARNING - GANs. Key Responsibilities: - Building deep learning models using TensorFlow/PyTorch - Collaborating with the team for testing and deployment - Good knowledge of Deep Learning Algorithms in NLP and Computer Vision - Creating and updating documentation - Implementing deep learning algorithms from scratch - Working on Computer Vision, Image processing, and TRANSFER LEARNING - GANs Qualifications Required: - Master or PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline - Relevant internship or work experience with data analysis - Experience with statistical software (R, Python, S-Plus, SAS, or similar) - Experience with database languages (e.g. SQL) In addition to the mentioned qualifications, you will research machine learning/data science topics for writing articles, assist with coding on Jupyter Notebook, work on short projects & assignments, and design/implement machine learning algorithms. Your passion for programming and deep learning/AI skills will be utilized to develop AI solutions in the computer vision domain using CNNs and a combination of deep neural networks. You will also handle object detection, recognition, image classification problems using machine learning and deep learning algorithms & transfer learning methods. Please note that the additional details about the company were not provided in the job description.,