RTH-Y FSS As an MLOps Engineer, you will be responsible for building and maintaining scalable, secure, and automated AI systems on the Azure cloud platform. You will enable seamless deployment, monitoring, and lifecycle management of AI models and services using Azure AI capabilities, ensuring reliability and compliance across environments. Your contributions will have a direct impact on our ability to deliver innovative solutions and drive business growth. You will combine your machine learning, software, and data engineering skills to design, develop, and deploy AI systems that solve business problems and provide value directly to our business unit and customers. This role involves collaborating with data scientists and engineering teams to implement CI/CD pipelines for AI, optimize workflows, and drive operational excellence for enterprise-grade AI solutions. Responsibilities and Activities Core Activities Design, implement, and maintain MLOps pipelines for AI/ML assets deployed as managed online endpoints in Azure Machine Learning. Automate deployment, monitoring, and lifecycle management of AI systems, including Azure Speech Services and OpenAI models. Collaborate with data scientists and engineering teams to integrate AI/ML assets into production environments. Implement CI/CD workflows for AI solutions using Azure DevOps and Azure CLI. Ensure compliance, security, and scalability of AI systems across environments. Build monitoring dashboards to track performance, data drift, and system health, and implement alerting and remediation strategies. Manage promotion of AI/ML assets (models, apps, containers) across development, staging, and production environments. Optimize resource utilization and manage cost efficiency for AI workloads in Azure. - IBMFG2JP00013843