Key Responsibilities

• Design, develop, and deploy machine learning models using Azure Databricks.
• Implement and manage Azure Databricks ML Flow for tracking and managing ML experiments.
• Apply ML Ops best practices to ensure robust, scalable model deployment.
• Deploy and manage LLMs and GenAI models on Databricks.
• Collaborate with data scientists and engineers to integrate ML models into production.
• Optimize and maintain ML models for high performance and scalability.
• Utilize PySpark, Python, and SQL for data processing and analysis.
• Conduct statistical analysis to support data-driven decision-making.
• Troubleshoot and resolve issues related to ML model deployment and performance.
• Stay current with the latest advancements in machine learning and cloud technologies.

Qualifications

• 7+ years of experience in ML model deployment using Azure Databricks.
• Proficiency in PySpark, Python, and SQL.
• Experience with Azure Databricks ML Flow and ML Ops best practices.
• Experience with deploying and managing LLMs and GenAI models on Databricks.
• Strong background in statistical analysis is a plus.
• Excellent problem-solving, communication, and teamwork skills.
• Bachelor’s degree in Computer Science, Data Science, or a related field (Master’s preferred).

Preferred Certificate

• Azure Databricks Data Engineer Professional Certification.
• Azure Databricks Machine Learning Professional Certificate.

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