Healthcare MLOps Engineer (Austin Onsite)

University of Texas at Austin; Austin (TX); On-site; USD 81,000 - 99,000; Full time

Job summary

The University of Texas at Austin is seeking an AI/Machine Engineer II to support development, deployment, and monitoring of machine learning models in production within a healthcare context. You will work under the Director of Data Intelligence and Decision Science to scale secure ML infrastructure, applying MLOps best practices and collaborating across teams.

Responsibilities include building deployment pipelines, enforcing governance, monitoring model performance, and coordinating with data

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering or related field.
• Minimum 2 years of relevant experience.
• Relevant education and experience may be substituted as appropriate.

Responsibilities

• Develop and refine ML deployment pipelines and workflows for production-grade model lifecycle governance and management.
• Implement lifecycle governance standards to support versioning and reproducibility.
• Optimize workflows for scalability and reliability.
• Implement and maintain monitoring systems to evaluate model performance, reliability, and drift.
• Detect and report model drift and anomalies.
• Create dashboards and alerts for stakeholders.

Job description

The University of Texas at Austin is seeking an AI/Machine Engineer II to support development, deployment, and monitoring of machine learning models in production within a healthcare context. You will work under the Director of Data Intelligence and Decision Science to scale secure ML infrastructure, applying MLOps best practices and collaborating across teams.

Responsibilities include building deployment pipelines, enforcing governance, monitoring model performance, and coordinating with data