MLOps Platform Engineer for Scalable Cloud Systems

Lead the optimization of ML platforms as a skilled MLOps Platform Engineer. Drive the development of scalable production systems in a hybrid work model while ensuring high availability and robust performance. This senior role demands expertise in production cloud-native environments with a strong focus on MLOps. You will collaborate with developers and infrastructure teams to maintain and enhance ML platforms, ensuring continuous training and deployment strategies are effectively implemented. Your contributions will significantly impact the operational excellence of AI-driven projects. Key Responsibilities: • Build and maintain scalable ML production systems • Manage core systems with updates and changes • Monitor and troubleshoot issues in production • Establish best practices for model versioning and tracking • Support systems during off hours when necessary Requirements: • 5+ years of MLOps experience in cloud environments • Proficient in Azure ML and AWS SageMaker • Hands-on expertise with Kubernetes and Docker • Knowledge of CI/CD pipelines and event streaming technologies • Strong programming skills in Python and Bash Elevate your career by enhancing MLOps practices and supporting advanced machine learning workflows within a collaborative environment.