Production ML Engineer - Healthcare AI & MLOps

Aimlroles; Austin (TX); On-site; USD 76,000 - 103,000; Full time

Job summary

University of Texas at Austin's Dell Medical School seeks an AI Engineer II to support ML deployment, monitoring, and governance in production healthcare environments. Reporting to the Director of Data Intelligence and Decision Science, this role emphasizes MLOps, model accuracy, security, and compliant data handling.

The position focuses on building scalable ML infrastructure, collaborating with data scientists and DevOps, and delivering reliable pipelines with emphasis on governance and

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
• Minimum 2 years of relevant experience.
• Relevant education and experience may be substituted as appropriate.
• 3+ years of experience in MLOps, DevOps, or ML engineering.
• Experience in healthcare or regulated environments.

Responsibilities

• Develops and refines ML deployment pipelines and workflows to support production-grade machine learning lifecycle governance and management.
• Implements lifecycle governance standards for versioning and reproducibility.
• Optimizes workflows for scalability and reliability.
• Collaborates with data scientists, software engineers, and DevOps teams to translate model requirements into operational solutions.
• Coordinates integration with APIs and application workflows.
• Participates in code reviews and design sessions.
• Designs and automates retraining, validation, and deployment processes to ensure model accuracy and responsiveness.
• Implements checks before deployment.
• Schedules retraining jobs based on triggers.
• Applies healthcare data governance and security protocols to ML systems, ensuring compliance with regulatory standards.
• Implements access controls and encryption.
• Supports compliance audits and documentation.
• Configures and optimizes cloud infrastructure for ML workloads, balancing performance and cost-efficiency.
• Tunes resource allocation for cost and performance.
• Monitors infrastructure utilization and scaling needs.
• Contributes to technical documentation, process improvement, and knowledge sharing across teams.
• Maintains technical documentation for ML workflows.
• Shares best practices and lessons learned.

Skills

ML engineering

DevOps practices

Python scripting

Model deployment

Education

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field

Tools

CI/CD pipelines

Cloud platforms

Kubernetes

Job description

University of Texas at Austin's Dell Medical School seeks an AI Engineer II to support ML deployment, monitoring, and governance in production healthcare environments. Reporting to the Director of Data Intelligence and Decision Science, this role emphasizes MLOps, model accuracy, security, and compliant data handling.

The position focuses on building scalable ML infrastructure, collaborating with data scientists and DevOps, and delivering reliable pipelines with emphasis on governance and