Roles

DevOps / MLOps Engineers

DevOps and MLOps Engineers streamline development and deployment pipelines to deliver software and machine learning solutions faster, safer, and more reliably. Koruteq’s team ensures infrastructure is scalable, automated, and performance-optimized for both traditional applications and AI-driven systems. They combine DevOps best practices (CI/CD pipelines, containerization, monitoring, cloud infrastructure management) with MLOps workflows (model training, versioning, deployment, monitoring in production). Skilled in tools like Docker, Kubernetes, Jenkins, GitHub Actions, Terraform, and Ansible, and cloud platforms such as AWS, Azure, and Google Cloud, they integrate ML technologies like MLflow, Kubeflow, DVC, and SageMaker for seamless ML model lifecycle management.

• CI/CD automation for software and ML pipelines
• Infrastructure as Code for scalable cloud environments
• Secure, reliable, and fault-tolerant systems
• ML model versioning, deployment, and monitoring
• Integrated DevOps and MLOps strategies for AI-driven businesses