Description

You will manage the end-to-end machine learning lifecycle on Azure cloud.

This role is on-site.

Responsibilities

• Design and implement cloud solutions and MLOps workflows on Azure.
• Build and orchestrate CI/CD pipelines using Azure DevOps or similar tools.
• Refactor, optimize, and monitor data science models, including containerization and versioning.
• Conduct testing, validation, and automation of data science models.
• Collaborate with data scientists and engineers to document processes and integrate APIs.

Required Skills

• 10 years of total professional experience.
• 5-8 years managing machine learning projects end-to-end.
• At least 18 months of recent, focused experience in MLOps.
• Proficiency with TensorFlow, PyTorch, Keras, and Scikit-Learn.
• Experience building pipelines using Azure Synapse and Databricks.
• Hands-on experience with Azure DataLake Gen2 and Unity Catalog.
• Strong background in software development and test automation.
• Bachelor's degree in Statistics, Economics, Computer Science, Mathematics, or Operations Research.

Preferred Skills

• Familiarity with ModelDB, Kubeflow, Pachyderm, or DVC.
• Experience supporting model builds for IDE-based models and AutoML tools.

Key Skills

Education

Bachelor's degree