# Pierce Stegman > Software Engineer at Google Location: New York, New York, United States Profile: https://flows.cv/piercestegman Machine learning software engineer. My academic research was in discrete signal processing and machine learning for brain-computer interface applications, with a focus on detecting imagined movements from brainwaves. GitHub: https://github.com/pwstegman Website: https://pwstegman.me ## Work Experience ### Software Engineer @ Google Jan 2023 – Present | New York, New York, United States ### Data Scientist @ Yext Jan 2020 – Jan 2023 | Arlington, Virginia, United States • Designed and implemented a reinforcement learning model to adaptively rerank search results. This became a key marketing point for Yext's search product. Conducted research and prototyped using Python 3, Pandas, and NumPy. Productionized the final model in Java. • Designed a feed-forward neural network to estimate which search results a user is most likely to click. Used Pandas and NumPy to gather and clean historic user interaction data. Used TensorFlow to train the model to output a probability estimate for a user click when given the BERT vector for a query and a result. • Domain expert for GPT-3 initiatives at Yext. Trained a large GPT-3-like model for few-shot natural language processing (NLP) tasks. Vetted hardware vendors, determined appropriate cost/performance tradeoff, optimized existing libraries (Megatron-LM + DeepSpeed and GPT-NeoX) for our hardware, and researched ideal prompt design and prediction parameters. • Designed a Vue.js web app for visualizing BERT self-attention. Used Python and PyTorch methods to reduce the attention matrices down to a single summary matrix. Exposed Python methods with a Flask REST API. This demo was used to sell our search product. • Designed a set of ML model serving components, allowing for quicker turnaround times on model deployment. Oversaw the modularization of our monolithic ML serving application, ensuring we can easily scale our codebase as we grow. • Wrote department-wide guidelines for system architecture design, ensuring all code followed a set of standards for easier collaboration and better maintainability. ### Frontend Web Developer | HHS Contract @ Nolij Consulting LLC Jan 2020 – Jan 2020 | Vienna, Virginia, United States • Developed an Angular application for the U.S. Dept. of Health and Human Services (HHS) to search through and filter contracts for health supplies using natural language. Users could rate filtered results as thumbs-up or down, which updated a reinforcement learning model. • Developed a data-labeling web app for machine learning research within HHS. ### Full Stack Developer @ Nolij Consulting LLC Jan 2015 – Jan 2020 | Vienna, Virginia • Implementation and maintenance of website • Automated employee workflows with scripts powered by Node.js ### Technical Writer | GSA Contract @ Nolij Consulting LLC Jan 2018 – Jan 2018 | Vienna, Virginia • Wrote technical documentation for GSA systems • Updated the online documentation system (reduced load time by 50%) ### Developer and Researcher @ Neurosity Jan 2019 – Jan 2020 | Greater New York City Area • Improved motor imagery classification accuracy by combining convolutional and recurrent networks. Used TensorFlow for data preprocessing, neural network design, training, and evaluation. • Implemented electroencephalography (EEG) signal processing methods in JavaScript. • Designed a Visual Studio Code extension in TypeScript which collected user brainwave data via a Neurosity EEG headset. The extension periodically prompted users to rate their productivity. This allowed us to conduct research into the associations between brainwaves and productivity. • Maintained a React-powered dashboard for EEG signal and neuro metric visualization. ### Research Assistant @ The University of Alabama Jan 2017 – Jan 2020 | Tuscaloosa, Alabama • Created a widely used JavaScript library for interacting with brain-computer interfaces and processing the incoming brainwave data in real time. • Implemented 30+ mathematical methods and algorithms for brainwave processing (bandpower, periodograms, independent component analysis, common spatial pattern, etc.). • Conducted EEG signal processing research using TensorFlow. ### Research Assistant @ The University of Alabama Jan 2017 – Jan 2017 | Tuscaloosa, Alabama • Researched signal processing techniques for high efficiency 360-degree video encoding • Created MATLAB scripts to analyze assorted video encoding methods • Performed statistical analysis on compressed data and used these insights to develop a more efficient video encoding method ### Student Researcher @ Mercedes-Benz U.S. International, Inc. Jan 2019 – Jan 2019 | Tuscaloosa, Alabama • Conducted Microsoft Kinect gesture recognition research as part of a partnership between The University of Alabama and MBUSI • Designed gesture-based device control for use in factory environments • MBUSI reported that the final system exceeded project expectations and was more accurate and easier to use than prior systems ## Education ### Master's degree in Computer Science The University of Alabama Jan 2019 – Jan 2020 ### Bachelor's degree in Computer Science The University of Alabama Jan 2016 – Jan 2019 ### Computer Science Thomas Jefferson High School for Science and Technology Jan 2012 – Jan 2016 ## Contact & Social - LinkedIn: https://linkedin.com/in/pwstegman - Website: https://pwstegman.me - GitHub: https://github.com/pwstegman --- Source: https://flows.cv/piercestegman JSON Resume: https://flows.cv/piercestegman/resume.json Last updated: 2026-03-23