MLOps Engineer

Role Overview

We are seeking an MLOps Engineer to bridge AI/ML model development and production deployment. The role focuses on building and operating MLOps infrastructure, deploying and monitoring production AI/ML workloads, and collaborating with data science and engineering teams.

Responsibilities:

• Own the end-to-end process of moving AI/ML solutions from experimentation into production environments
• Deploy, monitor, troubleshoot, and optimize machine learning workloads in production
• Ensure deployments are scalable, reliable, secure, and cost-effective using Azure cloud services
• Manage GPU-enabled environments for model inference and serving with Docker and Kubernetes
• Create and maintain CI/CD pipelines and Infrastructure-as-Code initiatives
• Implement monitoring, alerting, observability, and drift detection practices