About Me
Computer Science and Engineering graduate specializing in Artificial Intelligence and Machine Learning with hands-on experience building AI-powered applications, LLM-integrated systems, NLP solutions, and machine learning pipelines using Python, FastAPI, PyTorch, Hugging Face, LangChain, and LangGraph. Experienced in developing Retrieval-Augmented Generation (RAG) workflows, AI automation systems, REST APIs, and scalable backend services through internship experience and real-world projects. During my internship at CYPWNG Software Technologies, I worked on AI-driven healthcare applications, FastAPI services, machine learning workflows, RAG experiments, and cloud-native deployment practices. I contributed to backend development, API design, model evaluation, AI-assisted automation, and deployment pipelines while collaborating with cross-functional teams to deliver production-ready solutions. My projects include Intelligent Air Quality Prediction and Health Advisory Systems, Fake News Detection using NLP and Machine Learning, and Phishing Website Detection, where I applied machine learning, NLP, transformer-based models, Hugging Face, and data-driven decision-making techniques to solve real-world problems. I am particularly interested in Generative AI, AI Agents, Prompt Engineering, LLM Applications, RAG Architectures, and building intelligent systems that create measurable business impact. I am actively seeking opportunities as an AI Engineer, Generative AI Engineer, Machine Learning Engineer, NLP Engineer, or AI/ML Developer where I can contribute to innovative AI products while continuously expanding my expertise in modern AI technologies.
Skills & Technologies
Work Experience
AI Developer Intern
Designed and developed a full stack healthcare web application with Django that automated patient diagnosis, service scheduling, billing, and discount workflows, resulting in faster processing of patient records and fewer manual errors. Engineered RESTful APIs in Python (FastAPI) for secure patient data exchange, applying OAuth2 and role based access; migrated dual PostgreSQL schemas to Amazon RDS and introduced ElasticSearch indexing for rapid clinical document retrieval, improving query latency. Directed CI/CD pipeline using GitHub Actions, Docker, and Kubernetes to automate builds, tests, and blue green deployments across AWS and Azure; achieved 4 hour release cadence with deployment success for 8 sprint releases. Explored Anthropic Claude via LangChain to generate alternative diagnostic narratives, conducting A/B testing on patient cases and attaining a increase in clinician satisfaction scores. Designed backend APIs and workflow driven healthcare automation modules using Django, SQL databases, and REST integration patterns to improve operational efficiency and reduce manual processing overhead. Developed and tested PyTorch-based machine learning workflows for NLP-driven healthcare applications, implementing custom preprocessing, model evaluation, and performance monitoring pipelines to improve prediction reliability. Built and optimized FastAPI inference endpoints for AI-assisted healthcare services, incorporating request validation, response monitoring, and scalable deployment practices using Docker and Linux-based development environments.
Projects
Intelligent Air Quality Prediction and Health Advisory System
Developed a Streamlit-based machine learning web application that predicts AQI levels using real-time environmental data collected via API integration.
Fake News Detection System using NLP and Machine Learning
Built a supervised NLP-based text classification system to automatically detect and flag misleading or false news articles.
Phishing Website Detection using Machine Learning
Developed a phishing detection system using Python and Scikit-learn to classify malicious URLs.
Education
B. Tech
CSE(AI/ML)