***Do check my videos in the Featured Section to see what I do***I have almost 5 years of experience working in Artificial Intelligence/Computer Vision. Currently, I work as a Senior Machine Learning Engineer for a leading AI research firm, known for its pioneering work in machine learning and artificial intelligence. I've been in a full-time and fully remote position for almost a year. In this role, I apply my programming skills to develop computer vision solutions.Previously, I worked as a Data Analyst (Computer Vision) at Analytics, improving products and services for our customers by using advanced machine learning and computer vision techniques, creating and maintaining models, and onboarding compelling new data sets.Also, I was a Machine Learning Engineer at Stack Intel IO, where I built CV solutions for multiple projects.I have done the following projects during my professional experience:• Applied my programming skills, especially in Python and competitive programming, to teach AI how to program.• Made an application to detect facial coordinates and then applied image filters on the face using OpenCV• Detected Laptop/TV/Monitor Screens and then applied custom ad filters on screens using OpenCV based on demographics• AGRILIFT- an AI-based farm management system to enable precision farming for a sustainable world• Used OpenCV to make a virtual paint app that painted the captured screen according to the selected color• R&D on Super-Resolution GANs to improve S2 imagery• R&D on Canopy coverage and plant height using drone imagery using ODM (open drone map)• Image processing, manipulating tiff files for various tasks like NDVI calculation• Dataset Annotation and Augmentation for field segmentation• Projects related to object detection using Yolov4 and Deep sort and then applying custom filters using OpenCV• R&D on Kaldi and Bert for natural language processing• Built an application to detect human activities for bad posture that can lead to injuriesMy skill set includes but is not limited to:- Machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Trees, etc- Common data science toolkits, such as Pandas, NumPy, Scikit Learn, OpenCV- Applied statistical skills, such as distributions, statistical testing, regression, etc.- Deep Learning Techniques like Convolutional Neural networks, RNNs, LSTM- Natural Language Processing- Time Series Forecasting- Amazon Web Services (AWS)- Tensorflow- Python