Gregory Miller
Senior Software Engineer at Legacy Mutual Mortgage
McKinney, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolGregory Miller is a Senior Software Engineer based in McKinney, Texas, with over three decades of technology experience and 11 years focused on modern software roles. He architects and delivers customized mortgage banking solutions, integrating Encompass with Azure Power Platform, Office365, SharePoint and bespoke web portals while also handling deployments and SDK/API work. Gregory blends hands-on back-end development—evidenced by his contribution adding Azure Speech API support to a popular Python speech_recognition library—with leadership roles in community makerspaces and low-budget tech initiatives. He has held senior IT and executive roles across mortgage and financial services, demonstrating an uncommon mix of enterprise-scale systems design and grassroots technical stewardship. A longtime builder and tinkerer (he even constructs trebuchets), he brings practical engineering creativity and mentorship to teams and local tech communities. Outside of work he balances cloud architecture interests with family life, leadership at Plano Makerspace, and active open-source contributions.
11 years of coding experience
30 years of employment as a software developer
BS, Electronic Engineering, BS, Electronic Engineering at DeVry University
Github Skills (6)
apim10
audio10
speech-recognition10
api10
python10
documentation9
Programming languages (29)
Github contributions (5)
Uberi/speech_recognition
Oct 2018 - Oct 2018
Speech recognition module for Python, supporting several engines and APIs, online and offline.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 commits, 1 PR, 2 comments in 2 days
Contributions summary:Gregory focused on enhancing the speech recognition module, specifically integrating support for the Microsoft Azure Speech API. They implemented a new `recognize_azure` function, addressing the deprecation of the Bing Speech API. The user updated the documentation, including the examples, to reflect the changes and provide accurate information on API keys and usage. Their work improved the usability and compatibility of the speech recognition library with cloud-based speech-to-text services.
pythonspeech-recognitionaudiospeech-to-text
lastcoolnameleft/architecture-assessment
Feb 2019 - Oct 2019
Questions to ask during an Architecture Design Session
Contributions:45 commits, 44 pushes, 1 branch in 8 months
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