Join Scientific Games as a Staff Machine Learning Engineer and shape the future of ML platforms. Design an infrastructure that enables productive self-service for Data Scientists starting remotely and transitioning to a hybrid model. You will be responsible for architecting the organization’s first ML platform to empower Data Scientists.

In this role, your expertise will create frameworks for independent deployments, ensuring scalability and reliability. Collaborate with leadership to optimize the platform for organizational efficiency, all while setting high engineering standards for the team. Key Responsibilities:

- Architect the organization's initial ML platform
- Build frameworks to allow independent model production




- Develop capabilities for batch inference and real-time serving
- Establish CI/CD standards for ML deployments
- Mentor team members to elevate engineering standards

Requirements:

- Master’s degree in a related STEM field
- Over 5 years in ML-related engineering roles
- Experience in designing ML platform architecture
- Strong skills in Docker and Kubernetes
- Proven expertise in model lifecycle tooling and Python

Revolutionize ML deployment processes while mentoring the next generation of engineers at Scientific Games.

📌 Senior Machine Learning Engineer - Remote to Hybrid (Toronto)
🏢 Sglottery
📍 Toronto