ML Infrastructure Engineer (Azure AI)

Onebridge, a Marlabs Company, is an AI and data analytics consulting firm that strives to improve outcomes for the people we serve through data and technology. We have served some of the largest healthcare, life sciences, manufacturing, financial services, and government entities in the U.S. since 2005. We have an exciting opportunity for a highly skilled ML Infrastructure Engineer (Azure AI) to join an innovative and dynamic group of professionals at a company rated among the top “Best Places to Work” in Indianapolis since 2015.

This is a hybrid role with on-site work required 2-3 days per week in Indianapolis, IN.

ML Infrastructure Engineer (Azure AI) | About You

As an ML Infrastructure Engineer (Azure AI), you are responsible for designing, scaling, and optimizing cloud-based machine learning infrastructure to support enterprise and applied AI solutions. You have deep expertise in Azure AI services and cloud-native data engineering, excelling at building robust, maintainable systems that handle structured and unstructured datasets at scale. You partner closely with data scientists, analysts, and business stakeholders to operationalize AI models, ensuring reliable deployment and ongoing performance monitoring. You thrive in collaborative environments, taking ownership of end-to-end implementation while providing technical leadership on best practices for MLOps, APIs, and data pipelines. You are committed to leveraging innovative approaches to solve complex business challenges.

ML Infrastructure Engineer (Azure AI) | Day-to-Day

• Lead the design, deployment, and maintenance of Azure AI infrastructure and ML platforms, ensuring scalability, compliance, and reliability.
• Build and manage data pipelines for ingesting, storing, and processing structured and unstructured datasets.
• Develop and maintain APIs and system integrations with enterprise platforms.
• Implement MLOps best practices, including CI/CD pipelines, model deployment workflows, and monitoring model performance in production.
• Collaborate with data scientists, compliance experts, and product owners to operationalize AI solutions and deliver actionable insights.
• Support dashboards, reporting, and analytics using BI tools to translate complex data into clear insights for business teams.

ML Infrastructure Engineer (Azure AI) | Skills & Experience

• 5 years of experience in data engineering, machine learning, or AI-focused roles, with hands-on experience delivering scalable, cloud-based solutions.
• Proven experience delivering scalable AI/ML solutions using Azure AI, Azure ML, or AWS Bedrock.
• Hands-on experience designing and managing scalable cloud infrastructure and enterprise ML solutions.
• Strong programming skills in Python, SQL, and/or Scala, with the ability to deliver production-grade, testable code.
• Expertise in building and optimizing data pipelines, ETL processes, and large-scale data integration workflows.
• Experience implementing MLOps practices, including CI/CD, model monitoring, and deployment best practices.

A Best Place to Work in Indiana since 2015