Senior MLOps / DevOps Engineer

• Design, implement, and maintain scalable machine learning and data platform solutions on Azure.
• Drive best practices for CI/CD, containerization, and MLOps to support efficient model development and deployment.
• Collaborate with data science and engineering teams to enhance system scalability, reliability, and security.
• Support end-to-end machine learning lifecycle and deployment processes.

Responsibilities:

• Design and implement CI/CD pipelines using Azure DevOps.
• Architect and manage Kubernetes environments for machine learning workloads.
• Enable end-to-end MLOps workflows across Azure ML and Databricks platforms.
• Collaborate with cross-functional teams to improve system performance and reliability.
• Support deployment, monitoring, and maintenance of ML models in production.
• Ensure security and scalability of cloud-based solutions.

Skills:

• Strong expertise in Azure DevOps and CI/CD pipeline development.
• Experience with Kubernetes and container orchestration.
• Strong knowledge of Azure cloud services.
• Understanding of MLOps practices and ML lifecycle management.
• Experience with Azure ML and Databricks platforms.
• Strong problem-solving and analytical skills.

Should Have:

• Experience with infrastructure as code tools such as Terraform.
• Knowledge of monitoring and observability tools.
• Experience with machine learning model serving frameworks.

Qualification And Education:

• Bachelor s degree in Computer Science, Engineering, or a related field preferred, or equivalent experience.