Machine Learning Engineer — Cincinnati, OH

About the Role

A banking and financial services organization is seeking an ML Ops Engineer to join its Data Science Enablement team in Downtown Cincinnati. This role focuses on establishing a secure, automated deployment pipeline for an existing batch inference model and expanding the organization's machine learning operations capabilities.

The successful candidate will combine hands-on engineering with change management, architecture, and training. A key part of the role will be educating data scientists and other team members on MLOps practices while supporting the adoption of additional capabilities such as MLFlow, A/B testing, real-time endpoints, and Model Risk Management (MRM) automation.

Key Responsibilities

• Develop and implement a secure, automated deployment pipeline for an existing batch inference model.

• Educate and mentor data scientists and other team members on MLOps practices.

• Balance engineering responsibilities with change management and team training.

• Support architecture and training activities related to MLOps implementation.

• Expand MLOps capabilities through tools and techniques such as MLFlow, A/B testing, and real-time endpoints.

• Support further automation involving Model Risk Management (MRM).

Required Qualifications

• 3–5+ years of experience in machine learning and MLOps.

• Proven experience with AWS SageMaker.

• Experience building end-to-end machine learning models.

• Experience with data integration and management using IBM DB2, Snowflake, or similar databases.

• Strong understanding of CI/CD pipelines and automation tools.

• Proficiency in programming languages such as Python, R, SQL, and/or Java.

• Experience using DevOps tools such as Jira, Terraform, GitHub, and Jenkins.

• Knowledge of containerization and orchestration tools, including Docker and Kubernetes.

Preferred Qualifications

• Experience working in highly regulated industries such as banking, financial services, or healthcare.

Technical Skills

• AWS SageMaker.

• Python.

• SQL.

• MLOps.

• IBM DB2 and Snowflake.

• CI/CD pipelines and automation.

• Jira, Terraform, GitHub, and Jenkins.

• Docker and Kubernetes.

Location & Work Arrangement

• Downtown Cincinnati.

• Industry: Banking & Financial Services.

• Experience level: 3+ years.