Shawn Wang — Engineer · Founder · Quant
Engineers obsess over how to build; product people over what to build — I’ve never been able to weight one over the other. I’ve shipped startups as a solo founder and CTO, all on a foundation of software craft from my engineering years at AWS. Most recently I went down the rabbit hole of applied ML and quantitative trading — and here’s the result: a live algorithmic-trading system, trading autonomously on AWS.
Live — Real-time P&L · positions · epoch log
The Work
Instead of just reading about systematic trading, I built a complete one: research and modelling, rigorous validation, a trader-grade strategy, and the production system to run it. It trades real capital autonomously — around the clock on AWS.
Pulling it off meant living in three worlds at once and learning what each one guards: the engineering most ML scientists never build, the market instinct most engineers never develop, and the statistical rigor most traders never apply. The interesting work lives in that overlap.
Evidence
01
Calibrated, gradient-boosted models trained on years of high-frequency market data, validated with walk-forward cross-validation, probability calibration, information-coefficient and SHAP analysis, and permutation-based significance testing. The discipline that matters most: I found 17 promising signals and killed all 17 when they didn’t survive honest out-of-sample testing.
02
Live capital deployed on real markets today — not backtests, not paper trading. Running on Interactive Brokers and Polymarket. Real money, real results, publicly verifiable.
03
A small distributed system built for correctness under failure: a Nautilus-powered trading service, a purpose-built inference sidecar, durable settlement, and full observability — running live on AWS. Built by an ex-AWS distributed-systems engineer.
What's Next
Beyond the current system, I’ve been mapping what an AI-native version looks like — autonomous agents that form independent theses, challenge each other, and compete for allocation on top of the same research and execution foundation. It’s where the work points next, and the architecture is sketched out in the open.
Built by Shawn Wang — serial founder & CTO and ex-AWS engineer. I took the last half-year off to scratch a long-standing itch: learning quant finance and ML from the ground up. What I’m after next is a team of sharp people to build something great with. About
