Mohamed Chaaben
Montréal,Canada
Summary
Machine Learning Engineer with strong experience in data science. Proven ability to develop and deploy scalable ML models, automate workflows, and apply LLMs to real-world problems. Skilled in tools such as Azure DevOps, AWS SageMaker, and Docker. Focused on delivering measurable business impact.
Overview
4
4
years of professional experience
Work History
Machine Learning Intern
Bombardier Recreational Products
01.2025 - Current
- Predict vehicle failure time with 10% improved accuracy using tree-based models in Dataiku.
- Develop an LLM-based automatic categorization system for Salesforce tickets using both OpenAI’s API and a locally deployed LLaMA 3.2 1B model within Dataiku, resulting in increased client satisfaction.
- Design a logging and monitoring system in Dataiku to track key performance indicators, monitor system health, and detect model/data drift with alerting mechanisms.
- Keywords: LightGBM, Snowflake, Lamalndex, MLflow, FAISS
Machine Learning Engineering Intern
Buspas Inc.
01.2023 - 12.2024
- Automated onboarding of edge devices into a secure VPN with encrypted ID to enhance device authentication and reduce manual configuration.
- Built end-to-end CI/CD pipelines using Azure DevOps with YAML configuration and Azure Functions, accelerating deployment cycles and reducing release errors across multiple environments.
- Enabled LTE communication on IoT devices for SMS alerts using AT commands.
- Keywords: Docker, WiFi, Azure DevOps, CI/CD, AT commands, Azure Functions
Data Science Intern
Concordia University
05.2022 - 08.2022
- Developed a Graph Neural Network with Transformer-based attention to predict bus passenger flow using real-world transit data (STL Laval); Achieved 12% improvement in prediction accuracy compared to baseline models.
Computer Vision Intern
Sagemcom
10.2021 - 01.2022
- Trained a Faster R-CNN model for real-time driver monitoring (e.g., detecting unattended objects, drowsiness, and yawning), including dataset preparation and annotation, achieving 89% accuracy at 29 FPS.
- Keywords: Deep learning, PyTorch, Git, OpenCV, cuDNN
Education
Master of Applied Science - Information Systems Engineering
Concordia University
Montreal, QC12.2024
National Engineering Degree -
Higher School of Communication of Tunis
07.2022
Undergraduate Diploma - undefined
Preparatory Institute of Engineering Studies of Sfax
06.2019
Languages
French (native)
English (fluent)
Timeline
Machine Learning Intern
Bombardier Recreational Products
01.2025 - Current
Machine Learning Engineering Intern
Buspas Inc.
01.2023 - 12.2024
Data Science Intern
Concordia University
05.2022 - 08.2022
Computer Vision Intern
Sagemcom
10.2021 - 01.2022
Undergraduate Diploma - undefined
Preparatory Institute of Engineering Studies of Sfax
Master of Applied Science - Information Systems Engineering
Concordia University
National Engineering Degree -
Higher School of Communication of Tunis
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