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