💡 Full-Stack Engineer crafting scalable, intelligent, and user-driven software.
I am a software engineer that enjoys building clean, scalable, user-focused, and easily maintainable applications. From backend systems and APIs to frontend design and ML integrations, I love reaching across the full stack.
- Resume Screener: Flask + React + PostgreSQL + Pinecone + OpenAI/LangChain AI-powered resume screener that utilizes vectorization for similarity analysis of a resume and a job description.
- Improving my skills E2E
- Building efficient embeddings workflows with LangChain + Pinecone
- Experimenting with resume-job matching models using embeddings and semantic similarity
- TrackAJob: Java CLI application to track job applications. It utilizes OOP concepts of abstraction and encapsulation, has XML import and exportation, and practices using industry-standard programming such as using Logger instead of syso.
- PhotographicalDisplay: JS/HTML/CSS basic application to showcase photos I have taken throughout my travels/adult life. I may continue this further to have the photos be the doorway to themed galleries.
- ButtonPress: React + NodeJS + Firebase/Firestore + GCP application that simply counts the number of times a logged-in user has pressed a button. Serves to practice using React and GCP.
- RestaSwipe: MERN stack application for restaurant discovery in NYC via tinder-style swiping.
- Resume Screener: Flask + OpenAI application to give a best fit analysis between a user's resume and a job description.
- CommuteSmartAI: React (TS) + Fiber (Go) + Python + OpenAI NYC public transportation application. Think Google Maps, but better and a more intuitive navigational experience!
- ResNGo: React Native application for creating reservations
- MOVE Fellow @ Handshake AI - Enhancing AI model safety and contextual understanding
- Tech Consultant @ Datable Services - Building full-stack applications with React, Supabase, Go, and LovableAI.
- Software Engineer for AI Data Training @ ScaleAI - Refining outputs of state-of-the-art AI models through reinforcement learning and precise data annotation.
- My approach to development starts with understanding the full system before breaking it into modular, precise components. Once I’ve grasped the overall picture, I focus on making each piece clean, maintainable, and scalable. I believe that great code is both functional and understandable; clarity leads to longevity.