Responsibilities Design and build our central MLOps Platform covering the complete ML lifecycle Architect robust CI/CD workflows and self-service capabilities Partner with Data Scientists, ML Engineers, and Infrastructure teams Establish and evangelize MLOps best practices across the organization Optimize infrastructure costs and enhance observability Requirements 5+ years of experience in MLOps, ML Engineering, or DevOps Deep hands-on expertise with AWS SageMaker AI Strong proficiency in AWS cloud services, Python, and Terraform Solid understanding of the ML lifecycle and experience with containerization (Docker, Kubernetes) Exceptional communication skills Solution-oriented mindset with a passion for automation #J-18808-Ljbffr
