Key Responsibilities: implement and maintain endtoend ML pipelines for model training evaluation and with data scientists and software engineers to operationalize ML and maintain CI/CD pipelines for ML monitoring and logging solutions for ML ML infrastructure for performance scalability and compliance with data privacy and security regulationsRequired Skills and Qualifications: programming skills in Python with experience in ML in containerization technologies (Docker) and orchestration platforms (Kubernetes) in cloud platform (AWS) and their MLspecific with MLOps understanding of DevOps practices and tools (GitLab Artifactory Gitflow of data versioning and model versioning with monitoring and observability tools (Prometheus Grafana ELK stack) of distributed training with ML model serving frameworks (TensorFlow Serving TorchServe) of MLspecific testing and validation techniques11. Experience with Sagemaker Pipelines AWS CICD services AWS ML services API GW.