Sonder

Platform

• Lead the migration to a new in-house system leveraging the GraphQL Federation and build tools to facilitate the transition
• Lead the development of a comprehensive and high-level User Communication Platform
• Contribute to the implementation of a self-serve asynchronous communication system, and drive its adoption
• Design and develop a cloud-native DNS management service to automatically manage records for deployed applications

Sonder

Platform

• Contibute to the migration to Kubernetes from Heroku, extending the cluster with custom operators, and building core applications and libraries used by multiple services.
• Design and rollout a global Audit system to capture audit trails across the entire ecosystem

Revenue and Payment

• Design and build an invoicing system to automatically generate and communicate receipts to customers
• Redesign revenue-specific data models to increase their robustness and improve financial data accuracy

SSENSE

Acquisition and Localization

• Localize the website in China by introducing Chinese support and conforming to various Chinese government regulations
• Improve the SEO performance of the website
• Maintain the applications that support translation processes
• Support and facilitate the integration with affiliate marketing partners

Search

• Rebuild the search service in OOP (Typescript / Elasticsearch)
• Contribute to rewriting the monolithic application that serves the website into multiple micro services

Playster

Activity tracking and third party reporting

• Design, implement and develop the reporting system that generates custom consumption reports, verifies their accuracy, and delivers them to content providers and licensors
• Maintain the in-house tracking system, and develop new tracking features mainly used for Business Intelligence analysis

Université Laval

As part of my research, I looked into the problem of combinatorial optimization, especially combined with a powerful node ordering heuristic. The use case of my applied research was the problem of the scheduling of wood planning. My work leveraged machine learning to explore the space of solutions and detect areas where the optimal solution is likely to be encountered. The result of my research was a reinforcement learning based algorithm that solves wood planning scheduling problems considerably faster than the state of the art approach. For more details, check out the publication here.

Université Laval

I spent the last year of my bachelor program in computer science as an exchange student in Université Laval. There, I got the chance to enroll in a variety of interesting undergraduate as well as graduate level classes. The one that stood out the most is by far "Introduction to Robotics" where I got to build a microcontroller chip, mount it on top of a Roomba-like robot and program it to track and follow an object using infra-red and camera sensors.

ENSEM

During my bachelor program I learned the fundamentals of computer science, from low level concepts around electronics and networking to high level courses like algorithms and software engineering and some theoretical subjects in between like state machines, compilation, and game theory.