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Schedule Interview NowMy name is Abdul Samad S. and I have over 6 years years of experience in the tech industry. I specialize in the following technologies: Python, Large Language Model, Machine Learning, AI Chatbot, Data Science, etc.. I hold a degree in Bachelor's degree. Some of the notable projects I’ve worked on include: StockSeer-API - Stock Price Prediction, BestRAG - Python Library for Agentic Search RAG, QueryPLS: SQL Code Generation Agent, MediSync: Streamlined Hospital Management System. I am based in Karachi, Pakistan. I've successfully completed 4 projects while developing at Softaims.
I value a collaborative environment where shared knowledge leads to superior outcomes. I actively mentor junior team members, conduct thorough quality reviews, and champion engineering best practices across the team. I believe that the quality of the final product is a direct reflection of the team's cohesion and skill.
My experience at Softaims has refined my ability to effectively communicate complex technical concepts to non-technical stakeholders, ensuring project alignment from the outset. I am a strong believer in transparent processes and iterative delivery.
My main objective is to foster a culture of quality and accountability. I am motivated to contribute my expertise to projects that require not just technical skill, but also strong organizational and leadership abilities to succeed.
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I developed StockSeer-API, a FastAPI-based application for stock price prediction. Using machine learning models like RandomForestRegressor, ExtraTreesRegressor, LinearRegression, KNeighborsRegressor, and LSTM, the API predicts closing stock prices based on historical data fetched from Yahoo Finance. It supports data preprocessing, model training, and future price forecasting. StockSeer-API offers an interactive interface via FastAPI documentation for seamless integration. Users can train custom models and make predictions, with clear disclaimers about financial decision-making risks.
I created BestRAG, a Python library that efficiently stores and retrieves embeddings using hybrid Retrieval-Augmented Generation (RAG). By integrating dense, sparse, and late interaction embeddings, it ensures robust search performance for large datasets. Key features include PDF integration for seamless embedding storage and retrieval. BestRAG gained 1.3K+ downloads within its first month, showcasing its impact and usability. Developers have praised its simplicity, API integration, and performance, making it a valuable tool for document and data management solutions.
Developed QueryPLS, a cutting-edge web application that leverages advanced AI and Large Language Models (LLMs) to seamlessly convert natural language queries into accurate SQL statements. Recognized by LangChain for its innovation, QueryPLS ensures high accuracy, efficiency, and user-friendly interaction
MediSync is a comprehensive hospital management solution designed to address the challenges of efficient patient record management, doctor scheduling, and appointment coordination. Leveraging Django, HTML, CSS, JavaScript, and REST API, I developed this robust system to streamline healthcare facility operations. MediSync offers a user-friendly interface that centralizes patient and doctor data, automates appointment scheduling, and ensures secure data management.
Bachelor's degree in Software Engineering
2021-01-01-2025-01-01