# Brian Xie

> Software Engineer at Plaid

Location: San Francisco, California, United States
Profile: https://flows.cv/brianxie

Software Engineer at Plaid
Computer Science and Engineering, B.S. @ MIT '20
Interested in backend software engineering and computer systems.

## Work Experience
### Software Engineer @ Plaid
Jan 2021 – Present | San Francisco Bay Area

### Software Engineering Intern @ Plaid
Jan 2020 – Jan 2020
Developed + extensively load tested data pipeline and service from scratch to support increasing institution status demands. Go, MySQL, K8s, Amazon Kinesis, Typescript, React

### MIT Supertech, Researcher @ MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
Jan 2019 – Jan 2020
Developed and implemented Hybrid-PARAD, a provably work-efficient parallel algorithm and practical optimization that performs automatic differentiation for ML models. C/C++, Adept

### Software Developer Intern @ Five Rings Capital, LLC
Jan 2019 – Jan 2019
Built performant and robust trading systems by leveraging C++, algorithm & data structures design, and performance engineering.

### Core/Algo Wintern @ Hudson River Trading
Jan 2019 – Jan 2019
Optimized order book builder and matching engine to simulate US equities markets. Researched signals to predict cryptocurrency price movements, deployed risk-aware live trading strategies.

### Quantitative Trading Intern @ Old Mission Capital LLC
Jan 2018 – Jan 2018
Developed an options pricing simulator that provides an extendible, user-friendly, and performant platform for traders to easily test and evaluate new models. Leveraged Pandas, PyPy, and Slurm to reduce runtime from computationally infeasible to 3 hours per day.

### Computer Vision Engineer @ Synapse Technology Corporation
Jan 2018 – Jan 2018
Developed deep learning architectures to improve Synapse's automated threat detection system deployed at security checkpoints. Rewrote TensorFlow's object detection API to perform joint inference for dual-view x-ray images; received patent for "Multi-Perspective Detection of Objects".

### Affinity, Researcher @ MIT Media Lab
Jan 2017 – Jan 2017
Optimized deep convolutional neural networks for virtual drug screening and discovery. Used TensorFlow, Python, C, and SQLite to construct an extendable, easy-to-use machine learning API for molecular geometry, improving model development velocity by over 3x.


## Education
### BS in Computer Science
Massachusetts Institute of Technology
Jan 2016 – Jan 2020


## Contact & Social
- LinkedIn: https://linkedin.com/in/brian-xie-699475119
- Website: http://www.brianxie.me/

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Source: https://flows.cv/brianxie
JSON Resume: https://flows.cv/brianxie/resume.json
Last updated: 2026-03-23