Software Engineer — Trading Infra & ML

Hi, I'm Ryan Passaro.
I build low-latency systems that ship reliably at scale.

Headshot of Ryan Passaro

Flask/React SaaS, broker orchestration, JWT Auth, OCR pipelines, and GCP workloads — with measurable impact.

I’m an early-career software engineer focused on delivering impact. I learn fast, ship reliably, and make teams stronger. I’m here to move the needle and have a positive impact on those around me.

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Experience

Co-Founder & CTO · Taking Prophets

Jan 2025 – Present
  • Engineered Flask REST API to execute broker orders with sub-second latency.
  • Built secure PostgreSQL backend (AES-256, JWT Auth), zero incidents.
  • Parallelized orchestration with Python multiprocessing to reduce latency.
  • Developed real-time broker sync scripts cutting reconciliation work by 90%.
  • Scaled SaaS to 500+ subscribers, growing new user adoption 254% in 3 months.
  • Taking Prophets case study →

Software Engineering Intern · Archaide

Dec 2024 – May 2025
  • Deployed trading algorithms (Python, C++, JavaScript) with Interactive Brokers & Alpaca APIs, sustaining 99% uptime.
  • Designed order-management pipelines with error handling & reconciliation.
  • Integrated risk safeguards (position limits, kill-switches, rollbacks).
  • Automated onboarding workflows (Zapier + CRM), reducing manual work by 80%.
  • Archaide case study →

Software Engineering Intern · Quiver Quantitative

Mar 2024 – Aug 2024
  • Built OCR pipeline (Python + Tesseract) parsing thousands of filings at 95%+ accuracy.
  • Optimized preprocessing to reduce latency 30% and error rates.
  • Migrated workloads to GCP (Cloud Functions, BigQuery), boosting throughput 4× with auto-scaling.
  • Quiver case study →

Education

University of Texas at Austin

B.S. Computer Science & B.S. Economics — Expected May 2026

Projects

Personal Website (2025)

Built with Next.js (App Router) + React + TypeScript; styled with Tailwind and animated with Framer Motion. Includes a custom canvas parallax stars background and theme switching via next-themes; deployed on Vercel.

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Machine Learning Sports Forecasting (2024)

Trained XGBoost model with temporal backtesting, boosting accuracy by 20%. Automated ingestion/maintenance for 2M+ records (Python, SQLite, REST APIs).

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