

AI/ML Engineer who ships production AI tools and open-source libraries end to end. Skilled in Python, React, Node.js, and generative-AI integration (LLM orchestration, RAG, APIs, auth, payments, cloud deployment). Have independently designed, built, and launched multiple live full-stack AI applications and published open-source packages. Seeking AI/ML internships and full-stack engineering roles where I can own features from idea to deploy.
Years building software
Full-stack projects shipped
· Customer Segmentation — Retail (K-Means Clustering) · 12/2025 – 01/2026
Built a customer segmentation pipeline on a 200-customer retail dataset, deriving 5 actionable buyer personas (VIP, upsell, impulsive, conservative, budget) from income and spending score features. Applied StandardScaler normalization, used the Elbow Method to select k=5, and K-Means++ initialization for stable convergence; validated segments with Seaborn cluster visualizations.
· Intelligent Pathfinding (A* Search) · 12/2025
Implemented A* search in Python to navigate a 10×10 obstacle grid, using a Manhattan-distance heuristic and a heapq min-heap priority queue for efficient node expansion. Separated environment, algorithm, and visualization into clean OOP layers.
·Credit Card Fraud Detection Model · Group Project · 10/2025 – 11/2025
Co-developed a Random Forest-based machine learning model to automate credit card fraud detection, collaborating on code structure and algorithm optimization in Python for robust data analysis.