Design, develop, and maintain high-performance, scalable MLOps systems and pipelines that interact with AI models and systems.Build and operate end-to-end ML workflows on Azure Machine Learning, including training pipelines, experiment tracking, model registry, and managed online/batch endpoints.

·       Cooperate with cross-functional teams, including data scientists, AI researchers, and AI/ML engineers, to understand requirements, define project scope, and ensure alignment with business goals.Contribute technical expertise in evaluating, selecting, and implementing software technologies, tools, and frameworks in a cloud-native (Azure + Azure ML) environment.

·       Troubleshoot and resolve intricate software problems, ensuring optimal performance and reliability when interfacing with AI/ML systems.

·       Participate in software development project planning and estimation, ensuring efficient resource allocation and timely solution delivery.

·       Contribute to the development of continuous integration and continuous deployment (CI/CD) pipelines.

·       Contribute to the development of high-performance data pipelines, storage systems, and data processing solutions.

·       Implement monitoring and observability for deployed models and platform services (performance, data/model drift, reliability), with dashboards and reporting in Power BI and Grafana.

·       Contribute to the creation and maintenance of technical documentation, including design specifications, API documentation, data models, data flow diagrams, and user manuals. Mentor junior engineers and promote MLOps and software engineering best practices across the team.