Machine Learning Architect - Not an Active Opening, Building Talent Pipeline

Experience with IaC tools (CloudFormation, CDK, Terraform) Expert level experience in Amazon SageMaker and ML libraries (TensorFlow, MXNet, PyTorch, Scikit-learn) Strong understanding of ML concepts: feature engineering, hyperparameter tuning, optimization strategies Familiarity with MLOps tools (MLflow, Neptune, Comet)

Guide Cayliens and Customers through Agile ceremonies Translate customer requirements into a workable backlog of tickets Delegate tickets to engineers Lead requirements gathering, backlog grooming, and architecture discussions Apply understanding of DevOps pipelines Troubleshoot and resolve issues in customer environments Automate software testing Write production quality code, including unit and integration tests Deliver cloud native applications on AWS for customers Communicate and document designs, processes, and procedures Mentor peers, tackle new technologies Coach and mentor less experienced teammates