Drive innovation as a Staff Machine Learning Engineer at Scientific Games. Design and implement a cutting-edge ML platform architecture to empower Data Scientists for self-service model deployment.This role is pivotal in shaping the organization's first ML platform, requiring leadership and technical expertise. You will build frameworks that allow Data Scientists to operate independently while also establishing architectural standards and a comprehensive roadmap.



Your expertise will directly influence the company's machine learning strategy and deployment processes.Key Responsibilities:Define the architecture and roadmap for the ML platformDevelop self-service deployment frameworks for Data ScientistsEngineer reusable capabilities for model registry and orchestrationEstablish standards across SDKs, CI/CD, and developer workflowsMentor Senior MLEs and enhance platform thinkingRequirements:Master's in Computer Science, Engineering, or similar5+ years in ML engineering or platform engineeringProven experience with self-service ML toolingExpertise in Docker, Kubernetes, and cloud-native MLStrong Python engineering and ML lifecycle tools knowledgeLead the charge in building a robust machine learning platform that enhances organizational productivity at Scientific Games.#J-18808-Ljbffr

📌 Machine Learning Platform Architect - Scientific Games (Toronto)
🏢 Sglottery
📍 Toronto