5 Years of experience in an MLOps DevOps or similar engineering role focused on deploying and managing machine learning models. Strong proficiency in Python programming for data manipulation automation and handson experience with AWS including services such as EC2 S3 IAM CloudFormation/Terraform and containerization technologies (Docker Kubernetes/EKS).Experience with building and managing CI/CD pipelines (e.g. Jenkins GitLab CI/CD AWS CodePipeline).Understanding of machine learning concepts model evaluation metrics and deployment with monitoring and logging tools (e.g. CloudWatch Prometheus Grafana)Experience with version control systems (e.g. Git).Handson experience with AWS SageMaker for model building training and with AWS Glue for ETL and data with other MLOps tools and frameworks (e.g. MLflow Kubeflow Airflow).Experience with infrastructureascode tools beyond CloudFormation (e.g. Terraform).