Ethan Silverthorne

Ethan Silverthorne

Software Engineer

Software Engineer at KTAI, building PhotoFit AI — 400+ downloads, $2,400+ revenue
Backend Software Engineer at IBM (Summer 2026)
Computer Science @ Purdue University | Graduating December 2026
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About

Software Engineer at KTAI, where I build PhotoFit AI, an AI-powered fitness application available on the App Store and Play Store. I've launched this product with over 400 downloads and $2,400+ in revenue, demonstrating my ability to take products from concept to market.

I'm passionate about designing high-performance, scalable systems that solve real-world problems. Currently pursuing a Bachelor of Science in Computer Science at Purdue University with a 3.5 GPA, with minors in Mathematics and Management.

Technical Skills

Languages: Python, Java, TypeScript, C++, JavaScript, HTML/CSS
Frameworks: React Native, Node.js, Express.js, Tailwind CSS, Zustand
Tools & Platforms: Firebase, GitHub, MySQL, OpenAI API, RevenueCat, Expo
Concepts: OOP, Software Engineering, ML/AI Pipelines, Cloud Functions, CI/CD

Experience

Incoming

Software Engineering Intern, Cloud & Infrastructure

IBM

Summer 2026

Software Engineering Intern · Cloud & Infrastructure

Excited to join IBM’s Cloud & Infrastructure team next summer.

Founder & Software Engineer

KTAI

May 2025 - Present

Indianapolis, IN | Contract

  • Developed and launched PhotoFit AI fitness app using React Native, Zustand, and Firebase (Auth, Firestore, Cloud Functions), acquiring 450+ users, $2400+ revenue, and strong product-market fit in the first month across iOS and Android
  • Architected full-stack mobile application with serverless architecture, implementing AI workout generation via OpenAI API, equipment recognition, and payment integration with >99.99% uptime
  • Built AI pipeline with optimized prompt engineering and error handling, achieving 95%+ API success rate, while optimizing backend performance to reduce Cloud Function cold start latency by 2-5 seconds
  • Implemented agile development practices with rapid iteration based on feedback from 50+ beta testers, releasing 3 feature updates that increased user retention and session time by 40%
  • Established CI/CD pipeline using EAS and GitHub Actions, automating deployment processes and accelerating release cycles across App Store and Play Store

Server

Bridgewater Country Club

May 2022 - Present

Country Club

  • Delivered exceptional dining service to high-end clientele, maintaining the club's reputation for excellence through attention to detail and personalized guest experiences
  • Managed multiple tables simultaneously during peak service hours, demonstrating strong multitasking, time management, and organizational skills under pressure
  • Developed expertise in fine dining service standards, wine pairings, and menu knowledge to provide expert recommendations and accommodate diverse dietary preferences
  • Collaborated effectively with kitchen and service staff to ensure seamless operations and timely service delivery during private events and regular dining service
  • Maintained consistent positive guest relations, receiving recognition for professionalism and contributing to member retention and satisfaction

Projects

PhotoFit AI

App Store Play Store

AI-powered mobile fitness app that generates personalized workouts based on equipment and goals.

I designed, built, and shipped this application from the ground up, handling all aspects of development:

  • Product direction and feature decisions
  • Mobile app architecture using React Native and Expo Router
  • Backend systems with Firebase Auth, Firestore, and Cloud Functions
  • AI workflows for personalized workout generation
  • Subscription payments and lifecycle management with RevenueCat
  • Analytics, crash reporting, and production monitoring
  • App Store and Play Store review, compliance, and launch

Building PhotoFit AI shifted my perspective from feature-focused development to system thinking: reliability, scalability, failure modes, and user trust.

AI Model Catalog CLI

GitHub

Command-line tool for evaluating the trustworthiness of open-source AI/ML models.

The AI Model Catalog CLI assesses models from GitHub and Hugging Face by calculating a weighted NetScore across eight dimensions—from documentation and licensing to dataset quality and maintainability—helping teams make informed decisions about model adoption.

My Role

  • Backend Developer & API Integrator
  • Built scalable Python modules for GitHub and Hugging Face API integration
  • Implemented LLM-enhanced scoring using the Purdue GenAI Studio API
  • Added parallelized metric computation and auto-grader NDJSON output
  • Contributed to CI/CD setup, debug logging, and configuration

Key Features

  • Dual-source model analysis (GitHub & Hugging Face)
  • 8-dimensional trustworthiness scoring system
  • LLM-powered README and metadata evaluation
  • Parallel metric processing with built-in rate limiting
  • Auto-grader and NDJSON output for reproducible scoring
Tech Stack: Python, GitHub API, Hugging Face API, Purdue GenAI Studio API, Pytest, Pre-commit, CI/CD

Casino Simulator

GitHub

Object-oriented casino simulation demonstrating clean architecture and extensibility.

  • Designed 40+ OOP classes including Blackjack, Poker, and other casino games
  • Scalable architecture allowing new games to be added with minimal refactoring
  • Emphasizes encapsulation, design patterns, and modular design principles

IBM ML Certificate Projects

GitHub

Applied machine learning concepts through IBM's AI Engineering specialization.

  • Completed 20+ ML projects using Python, NumPy, and Pandas
  • Implemented supervised and unsupervised models, evaluation metrics, and ML pipelines

Contact

Let's connect. I'm always open to discussing opportunities, projects, or technology.

Download Resume LinkedIn GitHub emsilver987@gmail.com