MLOps Engineer - Data Modeling

RESPONSIBILITIES :

• Develop, productionize, and deploy scalable, resilient software solutions for operationalizing AI & ML.
• Deploy Machine Learning (ML) models and Large Language Models (LLM) securely and efficiently, both in the cloud and on-premises, using state of the art platforms, tools, and techniques.
• Provide effective model observability, monitoring, and metrics by instrumenting logging, dashboards, alerts, etc.
• In collaboration with Data Engineers, design and build pipelines for extraction, transformation, and loading of data from a variety of data sources for AI & ML models as well as RAG architectures for LLMs.
• Enable Data Scientists to work more efficiently by providing tools for experiment tracking and test automation.
• Ensure scalability of built solutions by developing and running rigorous load tests.
• Facilitate integration of AI & ML capabilities into user experience by building APIs, UIs, etc.
• Stay current on new developments in AI & ML frameworks, tools, techniques, and architectures available for solution development, both private and open source.
• Coach data scientists and data engineers on software development best practices to write scalable, maintainable, well-designed code.
• Agile Project Work
• Work in cross-functional agile teams of highly skilled software / machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate AI and MLOps solutions.
• Act as a positive champion for broader organization to develop stronger understanding of software design patterns that deliver scalable, maintainable, well- designed analytics solutions.
• Advocate for security and responsibility best practices and tools.
• Acts as an expert on complex technical topics that require cross-functional consultation.
• Perform other duties as required.

QUALIFICATIONS :

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