Hello, I’m Affaan Memon
Software Engineer
Python, Java, AI/ML, Cloud & Deployment
About Me
Hi, I’m Affaan Memon,
A Software Engineering graduate in Austin, TX with hands-on experience building full-stack Python, Java, and mobile applications.
I organize, prioritize, adapt under high-stress time constraints, and collaborate across teams.
What I do
I design, develop, administer, test, and support multi-architecture full-stack business applications and infrastructure.
Why I do it
I'm always looking to innovate and build the things that should be built.
Skills
I’m proficient in a range of modern skills and technologies. These are some of my main ones.
Languages and Frameworks
Tools and Platforms
AI Tooling
Development Practices
Certifications
I have a multitude of technical certifications from a variety of issuers ranging from Operating System to Development to the Cloud.
Education
University of Texas at Austin
Postgraduate Certification, Artificial Intelligence and Machine Learning, October 2024 - July 2025
Western Governors University
Bachelor of Science, Software Engineering, September 2022 - March 2024
Top Projects
I have a long list of projects over years of work; here are the top ones.
dotfiles
Published a macOS terminal configuration installable through a single Make target.
agency
Developed a Claude Code plugin managing session state for multi-agent teams, improving the sub-agent build experience.
Joblio - Local Job Application Tracker
Developed a self-hosted job application tracking application in Node.js with Docker deployment and a modular front end. Includes authentication, session management, request throttling, and tamper audit logging.
Stock Calculation Server
Python trading system built on three custom models with a voting pipeline and volatility tuning, reaching 86% precision. Adds paper trading, backtesting, multi-network failover, capital allocation, and crypto data across 13+ revisions. Actively maintained.
SuperKart - Retail Sales Revenue Forecaster
Dockerized Flask REST API using Random Forest and XGBoost trained on 8,763 transactions, paired with an interactive front end for single and batch revenue forecasts across product, location, and type filters.
Launch the back-end before the front-end.
HelmNet - Workplace Safety Classifier
Image classification models using transfer learning and CNNs to categorize workers wearing and not wearing helmets, supporting stronger operational safety practices.
NBFC Loan Default Hackathon
Placed 2nd by training a GPU-accelerated LightGBM and stacking ensemble on 93k+ loans, achieving 0.91 AUC. Improved performance through class weighting, an engineered income-to-loan ratio, and threshold tuning against PR curves.
Medical Assistant
- Developed an AI-powered RAG medical solution automating the use of medical manuals
- Enhanced diagnostic accuracy and treatment efficiency of illnesses
- Employed standardized care practice and decision making
- Reduced overload in healthcare settings
Vacation Manager Android Application
- Built and published a JUnit-tested Android app in Java with a multi-screen UI, scheduling, and push notifications.
- Implemented date-conflict and edge-case validation with persistent storage using the Room database.
- Shipped to the Google Play Store against security, backward-compatibility, and universal device standards.
DVD Rental Multi-Store Inventory Tracker
- Built a PostgreSQL-backed inventory system for a multi-location rental company with tiered roles and web tools.
- Designed reporting with triggers, procedures, and pgAgent to track stock and turnover, finding two issues.
Web-Based Spring Inventory Management Application
- Deployed a Java Spring MVC application for inventory tracking with CRUD operations backed by H2 and MySQL.
- Wrote custom controllers and five bean validators to enforce business rules on counts, pricing, and associations.