ML Ops Engineer

Job Title: ML Ops Engineer

Location: Remote

Position Type: Full-Time

Exp: 10

Job Description:

We are seeking an experienced ML Ops Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning operations, data governance, and Azure technologies. This role involves developing and maintaining ML solutions, managing data flows, and ensuring robust and efficient operations.

Key Responsibilities:

• Data Governance: Implement and oversee data governance practices to ensure data integrity, security, and compliance.
• Azure Databricks: Utilize Azure Databricks for large-scale data processing and machine learning model development.
• ML Flow Features: Develop and maintain ML flow features for tracking, managing, and optimizing machine learning experiments and models.
• Module Flow Management: Design and manage end-to-end module flows for machine learning pipelines to ensure smooth and scalable operations.
• Operations: Oversee daily operations, monitor performance, and troubleshoot issues within ML pipelines and data systems.
• Azure DevOps: Leverage Azure DevOps for continuous integration/continuous deployment (CI/CD) of machine learning models and infrastructure.

Qualifications:

• Bachelor s degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience with machine learning operations, data governance, and Azure technologies.
• Proficiency in Azure Databricks, ML Flow, and Azure DevOps.
• Strong understanding of data pipelines, module flow management, and operational best practices.
• Excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment.

Preferred Skills:

• Experience with other cloud platforms (AWS, Google Cloud Platform) is a plus.
• Knowledge of additional data processing tools and frameworks.
• Strong communication and project management skills

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