Description

You will design and manage machine learning lifecycles using Azure's ecosystem, building pipelines, implementing MLOps, and deploying scalable models.

This role is on-site.

Responsibilities

• Build and manage ML pipelines using Azure ML Studio and AutoML.
• Implement MLOps practices to automate model deployment and monitoring.
• Develop and maintain ETL workflows using Azure Data Factory, Databricks, and Synapse Analytics.
• Configure CI/CD pipelines for machine learning workflows via Azure DevOps, Jenkins, or GitHub Actions.
• Deploy and scale models within Kubernetes services.

Required Skills

• 12+ years of professional experience.
• Expertise in Python and Jupyter Notebooks.
• Hands-on experience with Azure Machine Learning (Azure ML Studio) and AutoML.
• Proficiency with MLOps tools and CI/CD for ML pipelines.
• Experience with Azure DevOps, Jenkins, or GitHub Actions.
• Experience with Kubernetes service.
• Proficiency in Azure Databricks and Databricks Pipelines.
• Experience with Azure Data Factory and Synapse Analytics.
• Degree in any field of study.

Preferred Skills

• Experience with Azure Blob storage, Azure Functions, or Azure Web Apps.
• Familiarity with Azure AI services and Azure Cognitive services.
• Telecom domain experience.

Key Skills

Education

Any Graduate