Principal Machine Learning Engineer - MLOps

We are looking for a Principal Machine Learning Engineer focused on ML Ops and ML Platform development. This engineer will join a centralized Machine Learning Engineering team, supporting scalable AI systems across Digital and Retail use cases. The ideal candidates will bring hands-on expertise in MLOps, distributed Machine Learning platforms, and experience working in cloud-native environments, especially Azure. Requirements 8+ years of relevant experience in Machine Learning, Data Engineering, or MLOps roles. Proven track record of building, deploying, and maintaining ML systems in production environments. Proficient with ML frameworks: PyTorch, TensorFlow, and Scikit-learn. Hands-on experience with MLflow, SageMaker, and Azure ML for model training, tracking, and deployment. Skilled in CI/CD pipelines for ML using GitHub Actions, Azure DevOps, and Terraform. Expertise in model observability, monitoring and drift detection. Experience building and managing ML pipelines using Airflow, Azure Data Factory, and related tools. Cloud infrastructure expertise with Azure (primary) and AWS (secondary). Containerization and orchestration using Docker and Kubernetes (AKS).