About the job
***English version below***
To be considered for this role, you must be based in Montreal due to the hybrid nature of the position.
The journey of travel goes beyond reaching a destination; it is woven with every memory we create along the way. At Plusgrade, we are committed to redefining the future of travel by collaborating with over 250 airlines, hotels, cruise lines, rail networks, and financial services to create significant new revenue streams through exceptional customer experiences. Founded on our core values of ambition, innovation, and collaboration, we are constantly driven to push boundaries, exceed expectations, and harness the best of each other. We foster a culture that believes our strength lies in unity, working together to build an extraordinary future in the travel space. Join us in transforming everyday travel into truly extraordinary experiences.
ABOUT THE ROLE:
As a Solution Architect for the Machine Learning Applications team, you will serve as the cornerstone of our ML ecosystem. You will be responsible for designing and overseeing the deployment of innovative platform solutions that address complex business challenges. This role requires a strong background in software development, high-level problem-solving skills, and the ability to align cross-functional teams (Data Science, Data Engineering, and Enterprise Architecture).
WHAT YOU WILL DO:
Reporting to the Director, ML Applications, Product Intelligence, you will:
• Lead end-to-end architectural design for machine learning applications, ensuring highly available, low-latency, scalable, robust, and reusable solutions.
• Collaborate closely with the Data Science team to ensure models are production-ready and aligned with application requirements.
• Work with the Data Engineering Architect to synchronize data pipelines, storage solutions, and feature delivery.
• Collaborate with the broader architecture community within the organization to achieve consensus and ensure consistency in technology standards.
• Design full-stack solutions covering both complex ML back-end logic and intuitive front-end layers.
• Actively contribute to the codebase by developing key components in Python along with integration logic.
• Manage technical delivery while adhering to the team's roadmap and ensuring alignment with business goals.
