Ethan Wang
Building systems that trade, scale, and think.
01 / About
I'm a computer science and mathematics student at Case Western Reserve University who builds things at the intersection of quantitative systems, AI infrastructure, and startups.
Currently co-founding Darch AI, where I architect high-throughput media pipelines serving 20M+ monthly impressions. Previously built AI tools at NIST. On the side, I run automated trading systems on prediction markets — reaching the top 100 on Kalshi's all-time crypto leaderboard.
Darch AI
02 / Experience
Darch AI
Co-Founder & Engineering Lead
Remote
- ▹Architected a hybrid microservices system (Python/FastAPI, Node.js) and high-throughput FFmpeg media pipeline to automate cross-platform content distribution, supporting 20M+ monthly impressions.
- ▹Optimized serverless resource allocation for 3,000+ monthly video jobs, maintaining 85%+ profit margins through aggressive caching and stateless execution.
- ▹Maintaining custom self-hosted infrastructure with modified authentication flows for multi-tenant B2B scheduling, while leading solution architecture for enterprise accounts.
National Institute of Standards and Technology (NIST)
Software Development Intern
Gaithersburg, MD
- ▹Built AI-driven internal tools including a help desk chatbot powered by a RAG pipeline, engineering document ingestion and optimizing retrieval strategies.
- ▹Developed and integrated a custom logging feature into an Open WebUI fork to enhance monitoring and debugging capabilities.
- ▹Collaborated with Boulder campus staff to deliver a wildfire evacuation dashboard based on stakeholder requirements.
03 / Projects
May 2024 – Present
Quantitative Trading on Kalshi
Automated trading system executing across prediction markets with market making, momentum, arbitrage, and latency-sensitive strategies.
- ▹3,500+ monthly trades totaling 500k contracts
- ▹Low-latency infrastructure processing hundreds of GBs of market data
- ▹Predictive models using Ornstein-Uhlenbeck SDEs, Hawkes processes, and modified Black-Scholes
February 2025
Orbit Chrome Extension
Multimodal semantic search engine for saved text, audio, and video using CLIP/CLAP embeddings.
- ▹Natural language queries over captured browser content
- ▹ChromaDB integration for real-time vector similarity search
04 / Skills
Languages
Frameworks
Infrastructure
05 / Contact
Let's build something.
Always interested in new opportunities, collaborations, and interesting problems.
ethan.wanq@gmail.com▌Designed & built by Ethan Wang