Role & responsibilities

Position: DevOps MLOps Engineer (Python / Machine Learning)

Role Summary

We are looking for an experienced DevOps–MLOps Engineer with solid expertise in Python, Machine Learning, and DevOps practices to build, deploy, automate, and maintain scalable machine learning solutions. The candidate will be responsible for developing end-to-end ML pipelines, implementing CI/CD automation, managing model deployments, and ensuring reliable production ML environments.

Key Responsibilities

- Design, develop, and maintain end-to-end MLOps pipelines for machine learning models.
- Develop Python scripts and automation frameworks for ML workflows.
- Build and manage CI/CD pipelines for ML model development, testing, and deployment.
- Deploy and manage ML models in production environments.
- Implement model versioning, experiment tracking, and model monitoring.
- Work with containerization technologies such as Docker and Kubernetes.
- Manage cloud-based ML infrastructure across AWS, Azure, or GCP.
- Automate model training, testing, deployment, and retraining workflows.
- Monitor model performance, data drift, and model degradation.
- Collaborate with Data Scientists, ML Engineers, and DevOps teams

📌 Infosys Hiring For MOPS Engineer (Bengaluru)
🏢 Glauben Technologies
📍 Bengaluru