What I work on today sits at the intersection of backend systems, large-scale data pipelines, and connected devices in the traffic and parking space. It's the kind of work I enjoy most: building systems that are technically deep, data-heavy, and closely tied to the real world. The company is now part of Tapco following its 2025 acquisition, but my day-to-day focus remains on improving the platform itself.
Most of my work revolves around backend services, ingestion and processing flows, and the movement of large volumes of device, event, and telemetry data through the system. I'm regularly involved in debugging production issues, investigating bottlenecks, and working on optimizations that improve throughput, scalability, and reliability. A lot of the work is about helping the platform keep up as new devices, new integrations, and new demands are added over time.
Back at LJEM Solutions, I had the chance to work on applied machine learning for hockey analytics, which was a particularly meaningful experience for me because it brought together several things I genuinely enjoy: engineering, data, and sport. I worked on models and data systems that turned historical game data into real-time forecasting and live analysis tools. That included building machine learning models for spatiotemporal hockey data, creating pipelines to transform raw event data into structured datasets for training and evaluation, and improving the experimentation workflow through better feature design, cleaner data partitioning, stronger reproducibility, and clearer internal documentation.
At the Ericsson Global AI Accelerator in Montreal, I worked as an AI Developer Intern and had the chance to deepen my interest in artificial intelligence and deep learning through hands-on industry experience. I collaborated with senior scientists on data pipelines and machine learning models, helped turn proprietary data into actionable insights, and built internal tools that improved efficiency around production resources. The experience gave me a strong appreciation for how AI work connects research, engineering, and real business impact.
Master's in Computer Science at Universite de Montreal. I pursued graduate studies in computer science, deepening my foundation in advanced computer science concepts and further developing my interest in software development and artificial intelligence.
My time at LJEM Solutions was where I first got to experience what it meant to build a SaaS product end to end. I was involved throughout the full lifecycle, from understanding requirements and shaping the design to implementing features, deploying services, and monitoring them in production. Along the way, I worked on backend systems and data storage, built an ABAC-based authorization module, created a real-time notification system, and contributed to a microservices architecture that improved scalability and made the product easier to grow. I also used Docker to simplify deployments and helped put coding standards and workflow documentation in place so the team could work more consistently and efficiently.
I started working at the Cummings Centre while I was still completing my bachelor's degree in software engineering, and it was one of my first real steps into the professional world of technology. It gave me hands-on experience not only in building software, but also in understanding how technology supports people and organizations in practice. I developed tailored information system solutions using Agile methods, helped improve reliability through automated testing and continuous integration, and used Docker to make deployments much faster and more efficient. I also provided IT support to more than 90 users, which strengthened my ability to solve problems quickly and deliver practical, user-focused solutions.
My Bachelor of Engineering in Software Engineering at Concordia University was where many of my core technical interests first came together. It was during those years that I developed a real appreciation for software design and algorithms, especially through the lectures of Professor Aiman Hanna, whose teaching left a strong impression on me. I also discovered my early interest in artificial intelligence through Professor Leila Kosseim's Natural Language Processing course, where I was introduced to AI and deep learning in a way that opened the door to a whole new area of curiosity for me.