Senior MLOps / DevOps Engineer

Machine Learning Engineer

Pay Range: $55hr - $60hr

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.

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.

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.

Experience with infrastructure as code tools such as Terraform.

Knowledge of monitoring and observability tools.

Experience with machine learning model serving frameworks.

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