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# MLOps / DevOps Engineer

- **Company:** Eliassen Group
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $145,600.0 - $168,480.0
- **Contract:** Permanent contract
- **Skills:** Cloud Computing, Software Quality, Continuous Integration, Software Debugging, DevOps, Github, Python (Programming Language), Machine Learning, Cloud Services, Azure Machine Learning, Systems Integration, Data Logging, Git, Containerization, Infrastructure Automation Frameworks, Deployment Automation, Machine Learning Operations, Terraform, Software Version Control, Data Pipelines
- **Published:** September 27, 2026
- **Apply:** https://www.juju.com/job/16_5e6b678c3

## About the Role

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance., * Strong experience with Terraform for infrastructure provisioning and automation.

 * Proficiency in Python for automation, tooling, and integrations.
 * Hands-on experience with GitHub Actions or similar CI/CD systems, including pipeline design and migration.
 * Strong understanding of Git operations, CI/CD principles, and DevOps practices.
 * Experience with AWS.
 * Experience with containerization and orchestration.
 * Familiarity with the machine learning lifecycle and model deployment workflows.
 * Experience supporting ML platforms, data pipelines, or model infrastructure preferred.
 * Strong communication skills and ability to work cross-functionally.
 * Problem-solving mindset with attention to detail and shared ownership.

## Description

* Design, build, and maintain cloud infrastructure using Terraform.
 * Develop and manage CI/CD pipelines with GitHub Actions for build, test, and deployment automation.
 * Support and improve MLOps platforms with a focus on reliability, scalability, and automation.
 * Debug and resolve issues across Terraform deployments, pipelines, and cloud services.
 * Automate environment provisioning, configuration, and lifecycle management.
 * Implement monitoring, logging, and alerting to ensure platform health and performance.
 * Collaborate with data scientists and engineers to streamline model deployment and promotion to production.
 * Contribute to repository management, version control practices, and code quality standards.
 * Drive developer experience improvements through tooling, documentation, and self-service capabilities.


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