👨💻 Full Stack Engineer | AI Enthusiast | Technical Leader
🌍 Pivoting back to my first love - building intelligent systems through code

After successfully bridging business and technology for years, I'm returning to my technical roots with renewed energy. I'm diving deep into modern AI/ML stacks, distributed systems, and developer tooling - and loving every minute of getting my hands back in the code.

• 🔭 Current Focus: Developing scalable applications and exploring advancements in machine learning and artificial intelligence.
• 🌱 Learning: Enhancing my skills by integrating AI tools and platforms into my daily workflows.
• ⚡ Fun Fact: I’m an avid cyclist and enjoy exploring new routes on weekends.
• 📫 How to Reach Me: Create an Issue or via LinkedIn

• Admitted via CCAT ≥40 (top 5% global cognitive threshold) to this $100M+ funded program
• Survived 80-100hr/week Survivor-style curriculum: Stanford-level ML coursework + shipping production code in 1-week "Speed Builds"
• Mastered AI-first engineering: Re-architected systems with LLM copilots while mentoring teams under high performance targets

1. AutoCRM:
   • Description: A production-grade CRM platform featuring real-time collaboration, military-grade security, and AI-driven insights, built on Supabase for scalable cloud infrastructure. Only my second react stack app, I fully deployed AutoCRM in only 50 development hours.
   • Technologies Used: React, TypeScript, Supabase, PostgreSQL, Tailwind CSS
   • Role: Full-Stack Architect, Developer
   • Key Features:
     • End-to-end type safety with Zod validation
     • Row-level security policies & real-time sync
     • Virtualized lists for 100k+ record datasets

1. UCSD ML/AI Capstone:
   • Description: A UCSD ML/AI capstone project developing a framework for testing Automatic Speech Recognition (ASR) models using baseball commentary audio retrieved from YouTube and metadata retrieved from ESPN.
   • Technologies Used: Python, ASR Models, PostgreSQL
   • Role: Data Analyst, Researcher
2. YT DLP ASYNC:
   • Description: An asynchronous, parallel-processing tool for fetching and processing YouTube audio data using yt-dlp, designed to aid scalable and efficient data collection and analysis for academic research projects.
   • Technologies Used: Python, yt-dlp, PostgreSQL
   • Role: Architect, Data Engineer, Developer
3. Whisper Chunk Transcribe:
   • Description: A Python application that utilizes OpenAI’s Whisper model to transcribe audio files in segments, enhancing accuracy and efficiency for lengthy recordings.
   • Technologies Used: Python, OpenAI Whisper, PostgreSQL
   • Role: AI Developer, Data Engineer

1. Uber Partner Events Website:
   • Description: A platform enabling Uber city operations teams to create and manage in-person events for drivers, fostering community engagement.
   • Technologies Used: PHP, Uber SSO integration, MySQL
   • Role: Product Manager, Designer

1. Website:
   • Description: The official website for the Kennesaw State University Lacrosse team, providing information on team members, game schedules, and news updates.
   • Technologies Used: C#, ASP.NET MVC, SQL Server
   • Role: Full-Stack Developer
   • Screenshots
2. Data Access Layer:
   • Description: A data access layer facilitating efficient database interactions for the KSU Lacrosse website.
   • Technologies Used: C#, Entity Framework & Data Model, SQL Server
   • Role: Backend Developer
3. MCLA Data Import:
   • Description: A tool to import and synchronize data from the Men’s Collegiate Lacrosse Association (MCLA) into the KSU Lacrosse website.
   • Technologies Used: C#, XML/XSD, SQL Server
   • Role: Backend Developer, Architect, Data Engineer

Core Stack • Languages: Python TypeScript SQL • AI/ML: PyTorch TensorFlow scikit-learn OpenAI API • Databases: PostgreSQL SQL Server BigQuery Pinecone • Cloud: AWS GCP • ML Frameworks: TensorFlow PyTorch Pandas • DevOps: Docker Kubernetes Terraform GitHub Linux • APIs: FastAPI Flask REST WebSocket Postman • Data Tools: Pandas NumPy Jupyter dbt Prefect • Async: asyncio • Frontend: React • Media: FFmpeg yt-dlp • Visualization: Tableau Grafana

Emerging Focus LLM Ops RAG Systems LangChain Distributed Systems Rust CI/CD Edge AI Airflow

After leadership roles in business and product, I realized my true passion lies in building technical solutions to hard problems. I thrive when:

• Architecting systems that scale
• Optimizing complex workflows and data pipelines
• Mentoring other developers
• Balancing engineering rigor with business impact

I'm actively seeking hands-on technical roles and collaborations in:

• Machine Learning Engineering
• AI Infrastructure
• Developer Tools
• Technical Leadership