⦿ Managed datasets through dedicated pipelines, ensuring organized and accessibledata.⦿ Implemented FastAPI, Docker, Pydantic, and PostgreSQL to wrap models, providinguser-friendly interfaces.⦿ Applied Python for image processing and computer vision tasks.⦿ Utilized Celery, Redis, and RabbitMQ for background tasks and queue-basedcommunication.⦿ Implemented FastAPI, Docker, Pydantic, and PostgreSQL to wrap models, providinguser-friendly interfaces.⦿ Handling deployments of deep learning models via docker, Kubernetes, mongo⦿ Resume Parsing and Question & Answering Techniques on unstructured data (Spacy,NLTK, Stanford NLP).⦿ Analyzed facial expression of a candidate for emotions, voice and stress level duringthe interview.⦿ Designing and developing machine learning and deep learning systems Runningmachine learning tests and experiments⦿ Perform statistical analysis and fine-tuning using test results

⦿ Developed natural language processing models in Python for phishing contentprediction using TF-IDF features and Random Forest, with three models inproduction.⦿ Integrated computer vision features with TF-IDF for enhanced model performance.⦿ Feature Engineering, Training, and Testing of Models, Finding New Techniques,reporting Precision and recall of models.⦿ Identify if a video has a live face or fake face (picture of another person, mobilescreen⦿ Extract Ocr from documents, Identify fields on Cards, Check the validity of a cardTrained Doc2vec on phishing content for word embedding.⦿ Proficient in Python, Linux, Shell scripting, AWK, handling large CSV files, and usingdevelopment tools like PyCharm, scikit-learn, and PyTorch, with experience in modelstacking techniques

⦿ Research on Document originality i.e Video or image contain a live card,⦿ Design a Deep learning architecture to validate if the document is not areplay attack⦿ Design a deep learning architecture to validate if the document is not aprint⦿ Design a system to check if fields of the cards are photo-shopped withsome tool or original

⦿ Research on Document originality i.e Video or image contain a live card,⦿ Design a Deep learning architecture to validate if the document is not areplay attack⦿ Design a deep learning architecture to validate if the document is not aprint⦿ Design a system to check if fields of the cards are photo-shopped withsome tool or original