Worked as an Associate Software Engineer in Machine Learning and Backend development. Worked on AI-based Document Processing (with/without metadata) Platform using different Optical Character Recognition (OCR) services. Helped to achieve productivity gains from 30% to 50% and extraction accuracy from 60% to 80%

• Designed, developed, tested, and deployed ML APIs for the software that uses these models.
• Web scraping with BeautifulSoup for Data Collection.
• Conversion of raw data into usable data by Data cleaning, Feature Engineering, Data Scaling, and Encoding with libraries such as NumPy, pandas, MinMaxScalar, and StandardScalar.
• Designed, and developed, and compared Recommendation System APIs with classification algorithms such as Random Forests, Naive-Bayes, and Decision Trees and selected the best algorithms with 95% Accuracy.
• Configured and extracted the required data with REGEX.
• Created an API with Django to send real-time JSON data to Azure Event Hub.
• Extracted City, State, and Country names with Named Entity Recognition (NER) using spacy and NLTK in NLP.
• NLP Sentiment Analysis of body of the email with TF-IDF and MNB.
• Testing with Postman.
• Docker and Kubernetes Deployment of APIs as Service.
• Developed PoC for email-domain identification with classification algorithms.

• Worked as a backend developer with ASP.NET, C#, and Microsoft SQL Server.
• Designed, developed, tested, and deployed backend APIs.
• Ran SQL scripts, made config changes in tables, and created stored procedures and tables according to requirements.
• Docker and Kubernetes deployment.
• Followed Agile methodology on Azure Boards with sprint planning, refinement, retrospective, and daily stand-up.