Mark Sturdevant
TEB- Supervisor at Dassault Falcon Jet
New York City Metropolitan Area United States
Summary
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Rockstar🎓
Top SchoolMark Sturdevant is an operations and technical leader with 11 years of experience managing rapid-response teams in the aviation sector and hands-on engineering work in cloud-based AI projects. As TEB Supervisor at Dassault Falcon Jet he leads AOG/rapid-response efforts out of the NYC metro area, bringing field-tested decision-making and team coordination to high-stakes situations. Complementing his aviation career, Mark has contributed full-stack and DevOps improvements to notable IBM open-source projects—integrating Watson services, modernizing Python apps, and enabling cloud deployments—demonstrating a rare blend of operational leadership and practical software engineering. He leverages an Aviation Management background from Vaughn College to connect systems thinking with user-focused automation, and his work often bridges frontline logistics with cloud-native tooling.
11 years of coding experience
3 years of employment as a software developer
Aviation Management, Aviation Management at Vaughn College of Aeronautics and TechnologyRiverside School of Aeronautics
Github Skills (30)
opencv10
javascript10
python10
ibm-cloud10
video-processing10
environment-variables10
flask-ask10
api10
computer-vision10
jupyter-notebook10
nodejs10
flask10
chatbot10
testing9
expressjs9
Programming languages (16)
Github contributions (5)
IBM/watson-voice-bot
Nov 2019 - Jan 2022
Create a Watson Assistant chatbot that uses voice over a web browser.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:1 review, 22 commits, 26 PRs in 2 years 2 months
Contributions summary:Mark primarily focused on enhancing the application's functionality and aligning it with modern Python and cloud standards. Their work involved updating the application to use Python 3.7, fixing indentation and flake8 errors, and upgrading the Watson SDK to version 4.0.1. They also integrated deployment options for Cloud Foundry and local environments, added an auto-upload feature for the skill, and made improvements to both the front-end display and the back-end conversation flow for an enhanced user experience.
chatbotwatson-assistantibmcodewatson-speech-to-textwatson-text-to-speech
IBM/watson-online-store
Mar 2017 - May 2021
Learn how to use Watson Assistant and Watson Discovery. This application demonstrates a simple abstraction of a chatbot interacting with a Cloudant NoSQL database, using a Slack UI.
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:55 commits, 78 PRs, 89 pushes in 4 years 3 months
Contributions summary:Mark significantly contributed to the back-end functionality of the Watson Online Store, focusing on integrating IBM Watson Assistant and Discovery services. Their work involved adding query capabilities to the Discovery service and modifying the application to handle responses from both Watson and Discovery. Moreover, the user demonstrated DevOps skills by setting up the application to be deployable to Bluemix, including configuring environment variables and integrating the services with the Flask-based web UI. They also performed code refactoring for better efficiency.
chatbotcloudantnosql-databaseslackwatson-assistant
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