Available for Summer 2026 internships

Hi, I'm Jonathan Wang.
I build systems that scale_

I build high-performance systems, distributed infrastructure, and ML pipelines that ship. Currently studying Math, CS, and Financial Engineering at Washington University in St. Louis.

See my work Contact me

St. Louis, MO

GitHub LinkedIn jonathanwang0321@gmail.com

PythonPyTorchRedisAWSPostgreSQLFastAPIDockerKubernetesDistributed Systems

About

Who I am

A brief look at my background, education, and how I think about software.

About me

I'm a junior at Washington University in St. Louis double-majoring in Mathematics & Computer Science and Financial Engineering. I love building backend systems that are fast, reliable, and thoughtfully designed — from vectorized backtesting engines to distributed task queues and real-time collaborative services.

I care deeply about writing correct, performant code and designing systems that are easy to reason about. I'm most at home in Python but I jump into C++, Java, or whatever the job calls for. Outside of code, I'm a quantitative-minded student who enjoys the overlap of math, CS, and finance.

3.84

Current GPA

Majors

Internships

Shipped Projects

Education

Washington University in St. Louis

St. Louis, MO · Expected May 2027

B.A. Mathematics & Computer Science

B.S. Financial Engineering

GPA 3.84 / 4.0·Dean's List (All Semesters)

Relevant Coursework

Data Structures & AlgorithmsObject-Oriented ProgrammingDatabase & Software System DesignMachine LearningLinear AlgebraProbability & StatisticsLogic & Discrete Math

Experience

Where I've worked

From telemetry at Bell Labs to high-performance backtesting at a quant-AI startup — a mix of big-company scale and early-stage ownership.

Software Engineer Intern @ InnovaAI Tech LLC

Dec 2025 – Feb 2026San Francisco, CA

Engineered a high-performance backtesting framework in Python using vectorized computation, Cython extensions, and multiprocessing; achieved a 10x speedup in simulation runtime, enabling evaluation of 100+ strategy configurations and saving 80+ researcher hours.
Designed a modular data ingestion and transformation pipeline on AWS (S3, EC2) to process 2TB of daily market data with configurable feature extraction, correlation filtering, and schema validation; encapsulated as a reusable utility, automating 90% of repeated work and saving 56+ hours per team.
Integrated deep learning model training with automated hyperparameter tuning via Optuna; built reproducible experiment tracking and evaluation pipelines, saving 10+ hours of manual tuning.

PythonCythonAWSMultiprocessingOptunaPyTorch

Co-Founder & Software Engineer @ MirrorJoy

Jun 2025 – Aug 2025San Francisco, CA

Architected a Snowflake-backed data platform with Python ETL pipelines to ingest, label, and organize 50,000+ image samples for downstream model training.
Built end-to-end model serving infrastructure in PyTorch with OpenCV preprocessing; applied quantization to reduce runtime by 38%, enabling sub-second inference latency in production.

SnowflakePyTorchOpenCVETLPython

Software Engineering Intern @ Nokia Bell Labs Shanghai

May 2024 – Aug 2024Shanghai, China

Built high-performance telemetry modules in Java and C++, reducing logging latency by 35% and system errors by 20%; extended protocol support across 500+ distributed network nodes.
Leveraged Java Concurrency Util, Netty, and gRPC to redesign the ID reservation subsystem by extending allocation windows and improving lock contention handling, decreasing peak-load resource contention by 25%.
Expanded automated test coverage by 15% through unit and integration tests across critical service paths, reducing regression defects in CI/CD pipelines and saving an average of 1.5 days per cycle.

JavaC++NettygRPCDistributed Systems

Projects

Selected work

Systems-level projects spanning distributed queues, real-time collaboration, and search infrastructure.

Distributed Task Queue

Jan 2026 – Feb 2026

A Redis-backed distributed task queue supporting async worker pools, task prioritization, and exactly-once execution.

Built in Python with async worker pools, task prioritization, and configurable concurrency using asyncio and multiprocessing.
Implemented retry policies with exponential backoff, dead-letter routing, and exactly-once execution via distributed Redis Lua locks.
Real-time monitoring dashboard (FastAPI + WebSockets) load-tested to 5,000 tasks/sec across 8 worker processes on AWS ECS.

PythonRedisFastAPIWebSocketsAWS ECSasyncio

Real-Time Collaborative Document API

Oct 2025 – Nov 2025

GraphQL backend for real-time collaborative document editing with operational transform and cross-instance sync.

WebSocket connections with Redis pub/sub for cross-instance synchronization and PostgreSQL for document persistence.
Operational transform (OT) conflict resolution with server-side version tracking and automatic merge.
RESTful API with JWT auth, RBAC, and rate limiting; pytest integration suite deployed via Docker Compose.

PythonGraphQLWebSocketsRedisPostgreSQLDocker

Web Search Engine from Scratch

Sep 2025

A full search engine with multithreaded crawling, inverted index, and TF-IDF ranking served via FastAPI.

Multithreaded web crawler (asyncio + aiohttp), inverted index in SQLite, and TF-IDF ranking via a FastAPI endpoint.
URL deduplication with bloom filters, robots.txt compliance, and politeness controls.
Indexed 50,000+ pages with sub-200ms average query response time.

PythonasyncioaiohttpSQLiteFastAPITF-IDF

Skills

Tools I build with

A pragmatic toolbox, refined through internships, research, and late-night side projects.

Languages

PythonSQLJavaC++RMATLAB

Frameworks

FastAPIFlaskPyTorchNumPypandasGraphQLREST APIs

Data & Infra

RedisPostgreSQLSQLiteSnowflakeDockerKubernetesLinuxGit

Cloud

AWS (S3, EC2, ECS)GCPAzure

Core Concepts

Distributed SystemsAsync ProgrammingObject-Oriented DesignMachine LearningConcurrency

Contact

Let's build something.

I'm actively looking for Summer 2026 software engineering internships. If you're hiring — or just want to chat about systems, quant, or side projects — I'd love to hear from you.