Rishit Murarka

Developed production-level AI interview application using Deep Learning models for candidate assessment and evaluation. Built comprehensive resume parsing system utilizing Natural Language Processing and Text Recognition algorithms. Trained and deployed sophisticated Deep Learning models for document analysis and information extraction and Implemented end-to-end machine learning pipeline from data preprocessing to model deployment and performance monitoring. Optimized Deep Learning models for accuracy and performance in real-world production environments. Conducted thorough performance evaluation against real-world test cases and benchmarked against competing solutions

Developed and deployed responsive web applications with focus on performance optimization and user experience Built scalable backend systems and APIs supporting real-time data processing and analysis Contributed to technical solution development and client-facing product demonstrations.

Co-founded SaaS platform implementing Machine Learning algorithms for automated lead generation and qualification. Developed scalable lead scoring algorithms and automated systems using Python and Machine Learning techniques. Built core software product from conception to deployment handling both Deep Learning model integration and system architecture. Sold the product and earned the revenue of over 4 lakhs with 97 percent margin.

Developed a plant classification model utilizing ResNet50, leveraging Roboflow for efficient dataset annotation and preprocessing of over 1000 images. Enhanced model performance through feature extraction and hyperparameter optimization, achieving significant accuracy gains. Built and secured Flask-based RESTful APIs with JWT middleware for authentication and authorization, implementing robust error handling and performance testing. Collaborated cross-functionally with clients and internal teams to align API features and deliverables with business goals, incorporating iterative feedback for continuous improvements. Documented workflows to ensure project reproducibility and ease of future enhancements. Technologies Used: ResNet50, Flask, JWT Middleware, Roboflow, Python, API Development, Hyperparameter Optimization