Join Scientific Games as a Staff Machine Learning Platform Architect in Toronto, transforming how Data Scientists deploy models. Lead the development of self-service machine learning solutions. This role focuses on architecting the foundational machine learning platform at Scientific Games, enabling Data Scientists to harness their capabilities for model deployment and experimentation.

You will establish engineering standards, create reusable tools, and guide a team of engineers. The impact of your work will be measured by the efficiency and independence of model deployment across the organization. Key Responsibilities:
Design target architecture for the ML platform
Create self-service deployment and orchestration frameworks




Develop observability and rollback capabilities for models
Mentor teams in software engineering quality and architecture
Partner with Data Science leaders for streamlined processes Requirements:
Master’s degree in relevant STEM field or equivalent
5+ years in ML or large-scale production systems
Experience with Docker, Kubernetes, and cloud-native setups
Familiarity with ML lifecycle tooling and CI/CD strategies
Leadership experience in architecture and mentoring roles Transform Scientific Games' ML landscape by applying your skills in Toronto.

📌 Staff Machine Learning Platform Architect Montreal (Canada)
🏢 Scientific Games
📍 Canada