Maxime Armstrong is a software engineer based in Montreal with 9+ years building web and data systems and a strong focus on machine learning, particularly NLP and computer vision. He blends hands-on backend development—recently contributing to Dagster's AWS ECS examples and test coverage—with leadership experience running teams of 2–12 and shaping architecture and CI/CD for production services. A solutions-oriented technologist, he has led open-source projects at MobilityData (data validators, databases, archiving) and helped operationalize ML research from UQAM where he won an eRisk challenge award. Graduating with honors from UQAM’s AI master’s program, he pairs academic rigor (GPA 4.3) with practical cloud-native skills across Python, AWS/GCP, Docker and Kubernetes. Maxime is notable for moving prototypes to production and for improving developer experience by expanding examples and tests in widely used orchestration tooling.
7 years of coding experience
10 years of employment as a software developer
Masters Computer Sciences Artificial Intelligence, Masters Computer Sciences Artificial Intelligence at UQAM | Université du Québec à Montréal
An orchestration platform for the development, production, and observation of data assets.
Role in this project:
Back-end Developer
Contributions:581 reviews, 1047 PRs, 3669 pushes in 2 years 1 month
Contributions summary:Maxime's contributions focused on updating and expanding the examples and test cases for the Dagster platform, specifically around the integration with AWS ECS for deployments. The user implemented examples for deploying ECS tasks using Definitions and incorporating features like run logs. The user modified several files to support the updated ECS deploy and to support features such as the replacement of NamedTuples with Pydantic.
Contributions:90 reviews, 331 commits, 182 PRs in 1 year 2 months
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