MLOps Engineer (Azure / Databricks / Python ML Platform Engineer)

Your responsibilities, Design, build, and optimize scalable machine learning solutions in cloud-based environments (Azure), Support end-to-end ML lifecycle: development, deployment, monitoring, and maintenance of ML models, Implement DevOps practices for ML workflows including CI/CD, version control, testing, and automation, Develop and maintain efficient, testable, and production-grade Python code for ML pipelines, Collaborate with data engineering teams to improve data ingestion, transformation, and model deployment processes, Design and implement monitoring, alerting, troubleshooting, and incident management for ML pipelines, Act as an ML Ops subject matter expert, advising stakeholders on scalability, infrastructure, and deployment strategies, Ensure best practices in ML system design, reliability, and performance optimization