Senior ML Engineer

Location: Bangalore
Experience: 5 Years
Primary Skills: MLOps Azure Machine Learning Python Azure Ecosystem

We are looking for an experienced Azure ML / MLOps Engineer with strong hands-on expertise in building deploying managing and monitoring machine learning models in production. The ideal candidate should have in-depth knowledge of Azure Machine Learning services Python-based ML workflows model deployment automation and production monitoring.

• Design build deploy and maintain scalable machine learning pipelines and production models using Azure Machine Learning.

• Manage Azure ML workspaces compute resources environments datastores data assets and model registries.

• Develop and automate ML jobs reusable components pipelines and endpoint deployments using the Azure ML Python SDK and Azure ML CLI.

• Deploy models through real-time online endpoints and batch endpoints ensuring reliability and scalability.

• Build CI/CD pipelines for machine learning workloads using GitHub Actions and Git-based development practices.

• Implement model monitoring performance tracking data/model drift detection alerting and production issue resolution.

• Work with Azure Storage (Blob Storage / ADLS Gen2) Azure Key Vault Azure Container Registry Microsoft Entra ID managed identities Azure Monitor and Application Insights.

• Develop modular tested production-grade Python code and manage containerized ML applications using Docker.

• Orchestrate machine learning workflows using Apache Airflow or similar workflow orchestration tools.

• Support infrastructure automation using Terraform and implement feature store solutions for ML feature management and reuse.

• Collaborate with data scientists data engineers and platform teams to operationalize ML models and improve deployment efficiency.

• 5 years of relevant experience in ML Engineering / MLOps.

• Strong hands-on experience with Azure Machine Learning and production model ownership.

• Expertise in Azure ML Python SDK Azure ML CLI jobs components pipelines and YAML-based configurations.

• Advanced Python programming including modular development testing packaging and shared repository practices.

• Experience with model deployment CI/CD Git Docker model monitoring and drift detection.

• Working knowledge of Azure cloud services and security integrations.

• Experience with workflow orchestration tools preferably Apache Airflow.

• Practical experience implementing or managing feature stores.

• Infrastructure as Code (IaC) experience using Terraform.

• Experience with automated model retraining model lifecycle management and production alerting.

• Experience improving ML platform reliability scalability and deployment automation.