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 platform
• Develop self-service deployment frameworks for Data Scientists
• Engineer reusable capabilities for model registry and orchestration
• Establish standards across SDKs, CI/CD, and developer workflows
• Mentor Senior MLEs and enhance platform thinking
Requirements:
• Master’s in Computer Science, Engineering, or similar
• 5+ years in ML engineering or platform engineering
• Proven experience with self-service ML tooling
• Expertise in Docker, Kubernetes, and cloud-native ML
• Robust Python engineering and ML lifecycle tools knowledge
Lead the charge in building a robust machine learning platform that enhances organizational productivity at Scientific Games.
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