Description

You will develop, deploy, and maintain machine learning models and pipelines within an Azure-based ecosystem to drive automation and predictive insights.

This role is on-site.

Responsibilities

• Analyze, design, and deploy ML models to automate processes and generate actionable insights.
• Enhance existing Azure ML pipelines and develop new models tied to calculated metrics.
• Implement synonym and file mapping intelligence to improve data usability.
• Collaborate with Data Engineers and Architects on data wrangling, transformation, and automation.
• Support MLOps practices including model deployment, monitoring, and lifecycle management.

Required Skills

• 5+ years of professional software engineering or data science experience.
• Strong proficiency in Python and SQL.
• Hands-on experience with TensorFlow and Sidekick.
• Experience with Azure Data Lake Gen2, Azure Data Factory, and Azure Synapse.
• Proficiency in T-SQL and SSIS.
• Proven experience building and maintaining ML pipelines and automation workflows.
• Ability to work independently and within cross-functional teams.

Preferred Skills

• Familiarity with Databricks and Medallion Architecture.
• Experience with MLOps tools and practices.
• Background in healthcare data or analytics.

Key Skills

Education

Any Gradute