About the role We are looking for a hands-on Senior MLOps Engineer with strong experience building, deploying, and maintaining production-grade machine learning systems. Requirements AWS SageMaker (Top Priority) Python & SQL Production MLOps / ML Engineering CI/CD/CT Pipelines & Model Deployment Model Monitoring, Registry & Feature Store Batch & Real-Time Inference Docker, Kubernetes & Terraform MLflow, Airflow or SageMaker Pipelines 10+ years of overall IT experience preferred 5+ years in ML/MLOps/Data Engineering 3+ years supporting production ML systems Banking / Financial Services experience preferred Must be authorized to work without sponsorship Candidates must be comfortable with 100% onsite work and an onsite client interview. Schedule W2 | 6+ Months (Long-Term Extension Possible) 100% Onsite How to apply Share your updated resume. Location Cincinnati, OH