As a skilled Backend Developer with expertise in Python, FastAPI, and Django, I have a strong foundation in developing and optimizing API endpoints, implementing efficient data processing scripts, and integrating with various databases including MySQL, PostgreSQL, and vector databases like FAISS. My experience extends to cloud platforms such as Google Cloud Platform (GCP) and Amazon Web Services (AWS). I have demonstrated the ability to create scalable solutions for healthcare applications and implement advanced features like Retrieval-Augmented Generation (RAG) systems.
Developed and optimized API endpoints using FastAPI for improved performance and scalability. Engineered efficient Python scripts to automate data extraction and entry processes. Created AI-driven solutions for differential diagnosis using advanced prompt engineering techniques. Architected and implemented a hybrid Retrieval-Augmented Generation (RAG) system leveraging FAISS (vector DB) and Neo4j (graph DB).
Engineered a mental health chatbot by fine-tuning LLaMA2 and LLaMA3 models using Hugging Face Transformers with PEFT and QLoRA. Designed and implemented an advanced chatbot using OpenAI API, employing sophisticated prompt engineering for domain-specific applications. Developed and deployed an MVP using Streamlit, creating an interactive and user-friendly interface.
Conceptualized and implemented data science solutions to address complex business challenges. Conducted comprehensive exploratory data analysis (EDA) on large-scale datasets. Developed and trained machine learning models for both regression and classification tasks.
Spearheaded the development and maintenance of the official IEEE SCT SB website and subcommittee sites using WordPress. Orchestrated content updates, implemented new features, and ensured optimal website performance and user experience.
Comprehensive skill set spanning AI, Machine Learning, database management systems, app development, web development, statistics, and system commands with also working in hands-on projects to solve real-world problems using data-driven approaches.
Engineered a semantic search system for efficient retrieval of relevant resumes from large collections using FAISS and Hugging Face embeddings. Integrated LangChain for natural language query processing and implemented RAG for enhanced accuracy. Utilized Cohere reranker to significantly improve retrieval accuracy. Implemented features for highlighting search queries and generating summaries for top-matching resumes.
Designed and implemented a deep learning model for detecting botnet attacks from raw network traffic data. Achieved high accuracy in distinguishing between malicious and benign network traffic. Developed an intuitive user interface using Tkinter, mimicking antivirus software functionality.
Successfully fine-tuned LLaMA 2 and LLaMA 3 models using PEFT and QLoRA techniques for a specialized mental health chatbot. Enhanced chatbot performance through the implementation of advanced prompt engineering strategies.
Developed a full-stack web application for downloading YouTube videos, leveraging Django and Pytube. Implemented a user-friendly interface allowing video downloads in various formats. Successfully deployed and hosted the application using Vercel.