# Scott Bauersfeld

> Software Engineer at Databricks

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

I'm a curious and hard-working software engineer who is passionate about building complex systems at large scales. I am always looking to learn new things, so I decided to pursue a Master's degree to learn more about deep learning and distributed systems. I have hands-on experience with building deep learning models through research at UCLA, and I have software development experience through internships at Amazon, Qualcomm, and Symantec. Outside of work, research, and classes, I enjoy hiking, camping, backpacking, and exercising.

## Work Experience
### Senior Software Engineer @ Databricks
Jan 2024 – Present

### Software Engineer @ Databricks
Jan 2021 – Jan 2024

### Research Assistant at Neural Computation and Engineering Laboratory @ University of California, Los Angeles
Jan 2019 – Jan 2021
Developing non-invasive brain-machine interfaces capable of predicting imagined movement with deep learning
- Implemented deep convolutional and recurrent neural networks to predict imagined directional movements
- Preprocessed EEG signal data to reduce noise and improve accuracy

### SDE Intern @ Amazon
Jan 2020 – Jan 2020
Creating a web tool to identify AWS service failures and decrease remediation time.
- Developed a REST API to aggregate 10,000 service logs per minute from 20 AWS regions spanning 6 continents
- Designed and implemented a serverless backend with AWS API Gateway, Lambda, and Node.js.
- Created an interactive frontend with Typescript, React, and Redux to display tabular information.
- Integrated AWS CloudFront to reduce latency, Cognito to authenticate users, and CloudFormation to programmatically deploy infrastructure.

### Software Engineering and Machine Learning Intern @ Qualcomm
Jan 2019 – Jan 2019 | Greater San Diego Area
Accelerated ONNX Runtime to maximize inference rates and minimize power consumption for computer vision applications on Qualcomm mobile devices.
- Implemented an execution provider to perform inferencing on ONNX machine learning models
- Quantized deep learning models to reduce inference latency by 60x for deep convolutional neural networks such as MobileNet and ResNet

### Software Engineering Intern @ Symantec
Jan 2018 – Jan 2018 | Culver City
Participated in Agile development of C++ API for virus-scanning software that reduced development time for new products by 4 months
- Added capability to remove or replace virus-infected files with a popular virus-scanning tool
- Provided 100% unit test coverage in C++ and integration tests in Python


## Education
### Bachelor of Science in Computer Engineering
UCLA

### Master of Science in Computer Science
UCLA


## Contact & Social
- LinkedIn: https://linkedin.com/in/scott-bauersfeld-45a447155

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Source: https://flows.cv/scottbauersfeld
JSON Resume: https://flows.cv/scottbauersfeld/resume.json
Last updated: 2026-03-22