MLOps Engineer

Job Summary (List Format): - Architect and maintain scalable MLOps pipelines for model training, deployment, and monitoring. - Lead implementation of containerized ML workloads using Kubernetes. - Collaborate with data scientists and engineers to productionize ML models. - Automate model lifecycle management, including versioning, rollback, and performance tracking. - Ensure high availability, security, and compliance of ML systems. - Develop infrastructure as code using tools such as Terraform…