Justin Essert
Lead Machine Learning Engineer - ML As A Service at Capital One
Richmond, Virginia, United States
Summary
👤
Senior🎓
Top SchoolJustin Essert is a Lead Machine Learning Engineer with nine years of experience specializing in time series modeling and production ML platforms. Based in Richmond, VA, he leads ML-as-a-Service efforts at Capital One, focusing on reusable, modular tooling that accelerates cross-team adoption and long-term maintainability. Known as an effective communicator and mentor, he frequently drives collaborations that align product and engineering goals while coaching junior developers in modeling and software engineering best practices. His background blends an MS in Machine Learning & Signal Processing with hands-on contributions to testing infrastructure for widely used ML libraries like keras-preprocessing, reflecting a practical emphasis on reliable, well-tested systems.
9 years of coding experience
4 years of employment as a software developer
Master of Science - MS Machine Learning & Signal Processing, Master of Science - MS Machine Learning & Signal Processing at University of Wisconsin-MadisonHigh School, High School at Middleton High School
Stackoverflow
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Github Skills (6)
testing10
keras10
pytest10
python10
image-processing10
computer-vision9
Programming languages (4)
Github contributions (5)
keras-team/keras-preprocessing
Jun 2018 - Jun 2018
Utilities for working with image data, text data, and sequence data.
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:26 commits, 1 PR, 4 comments in 12 days
Contributions summary:Justin primarily contributed to the testing infrastructure of the `keras-preprocessing` library, adding and modifying tests to ensure functionality. Their contributions included creating tests for RGBA image support, fixing existing test parameters, and updating tests to use the new `load_img` format. They focused on thoroughly testing various image loading and processing functions, including those handling grayscale, RGB, and RGBA images, and also testing image transformations.
text-datasequencepythonimage-data
justinessert/mascot-bracket-constructor
Feb 2022 - Feb 2024
Utility to create a mascot bracket
Contributions:4 PRs, 20 pushes, 5 branches in 2 years
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