Senior ML Ops Engineer

Kforce has a client in Charlotte, NC that is seeking a Senior ML Ops Engineer. Summary: We're seeking an experienced MLOps Engineer with a primary focus on cloud automation, CI/CD, and machine learning deployment pipelines. This is not a data science or ML engineering role-we need someone rooted in MLOps and infrastructure automation, with a strong track record of supporting model operationalization at scale. You'll work closely with data scientists to deploy ML models, manage infrastructure as code, and streamline end-to-end workflows using AWS and GitHub Actions. Duties:

• Build and optimize CI/CD pipelines to deploy ML models to production environments
• Own infrastructure automation using Terraform and AWS services
• Automate ML model deployment workflows using Python and shell scripting
• Collaborate with data scientists to streamline model training and inference workflows
• Manage containerized deployments using ECS, EKS, and Lambda
• Implement workflow orchestration with AWS Step Functions and Glue
• Drive MLOps best practices and ensure compliance with Agile SDLC processes
• Strong Python skills for scripting, automation, and debugging ML deployment pipelines
• Strong AWS expertise: SageMaker, Glue, Lambda, ECS, EKS, IAM, Step Functions
• Hands-on experience with Terraform for infrastructure as code
• Proven skill in GitHub and GitHub Actions for workflow automation
• Python proficiency for scripting, debugging, and automation
• Solid background in shell scripting for deployment and maintenance tasks
• Demonstrated success supporting ML model deployment in production
• Senior-level candidates: experience taking ownership of MLOps solution design and troubleshooting