Hi there! I am,

Leo Tsao
I build tools, infra, and stuff.

Software engineer at AWS working on large-scale distributed systems. Focused on developer tooling and platform infrastructure.

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About

I design and build reliable backend systems that operate at scale. My work has focused on distributed orchestration platforms, workflow scheduling, and developer productivity tooling across globally deployed environments.

I care deeply about the developer experience layer — the frameworks, tooling, and platform primitives that let engineering teams move fast without breaking things.

Outside of AWS, I'm exploring infrastructure gaps in the AI ecosystem — particularly around cost observability, deployment velocity, and multi-agent coordination.

Selected Work

End-to-End ML Pipeline — In Progress

MLOps pipeline for income classification, covering data ingestion, model training, serving, and observability.

→ Trained and compared Logistic Regression and XGBoost with full MLflow experiment tracking
→ Served predictions via FastAPI with Prometheus metrics and Grafana dashboards
→ Containerized full stack with Docker Compose — inference, MLflow, Prometheus, and Grafana

MLOps Python FastAPI MLflow Docker Prometheus Grafana

Travel Journal Android App

Led a team of 5 to build an Android app that lets users document travels and generate customizable single-page journals — won honorable mention at the 2021 Allring Competition.

→ Deployed API layers on Firebase and Google Cloud Functions with a Chrome Extension for bookmarking
→ Built web crawlers and NLP modules to extract scenic spots from bookmarked blog articles
→ Won honorable mention at the 2021 Allring Competition

Android Kotlin Python GCP Firebase NLP

Speech Income & Expense Tracker

Led a team of 4 to build a Python desktop app that extracts items and money amounts from spoken sentences using a custom deep learning model.

→ Designed a deep learning model combining PyTorch and Keras for spoken financial entity extraction
→ Conducted independent research on NLP and speech processing literature to inform model design
→ Received the highest score from peer review, presented as a poster

Python PyTorch Keras Deep Learning NLP Speech

News Article Simplification for Children

Built a system that simplifies news articles for young readers by replacing difficult words with simpler counterparts using BERT and word embeddings.

→ Built a child-oriented lexical resource achieving 75% vocabulary coverage across evaluated articles
→ Preserved semantic fidelity while reducing overall article complexity
→ Improved readability and accessibility for elementary-level readers

Python BERT Word Embeddings NLP

Food Waste Reduction Platform

Collaborated with a team of 5 to build a full-stack web application connecting food donors with recipients to reduce waste.

→ Led development of the API Gateway and Subscription Service, delivered within 2 months
→ Managed data storage with Firebase and containerization with Docker
→ Built on a Service-Oriented Architecture with React and FastAPI

React JavaScript TailwindCSS FastAPI Firebase Docker

Skills

Languages

Python

Java

Kotlin

JavaScript

TypeScript

Frameworks & Libraries

React

FastAPI

Spring

PyTorch

Keras

scikit-learn

Infra & DevOps

AWS

Docker

Firebase

Prometheus

Grafana

Data & ML

MLflow

pandas

Interests

AI Infrastructure
Distributed Systems
Developer Productivity Platforms
Intelligent Agents
ML Platform Architecture
Technical Founding Opportunities

Contact