AI/MLOps Engineer for Healthcare ML

The 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 Engineer II to join the Dell Medical School in Austin, TX. This exempt role focuses on building and maintaining ML infrastructure, deployment, and governance for production models in a healthcare setting.

You will collaborate with data scientists, software engineers, and DevOps to automate retraining, monitor performance, and ensure security/compliance of ML workflows.

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.

Responsibilities

• Develops and refines ML deployment pipelines for production-grade machine learning lifecycle governance and management.
• Implements lifecycle governance standards for versioning and reproducibility.
• Optimizes workflows for scalability and reliability.
• Implements monitoring systems to assess model performance, reliability, and drift.
• Detects and reports model drift and anomalies.
• Generates dashboards and alerts for stakeholders.
• 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.
• Assists with proof-of-concept evaluations for new MLOps tools.
• Participates in post-mortem reviews for ML pipeline incidents.
• Supports periodic updates to model documentation and compliance records.
• Adheres to internal controls and reporting structure.
• Performs related duties as required.
• Communicates and collaborates effectively across technical and non-technical teams.
• Participates in reviews and stand-ups to share updates.
• Co-develops APIs and integration points.

Skills

Programming

ML concepts

CI/CD

Cloud

Education

Bachelor’s degree in CS/DS/Engineering

Tools

CI/CD tools

Cloud platforms

Container orchestration

Job description

The University of Texas at Austin is seeking an AI Engineer II to join the Dell Medical School in Austin, TX. This exempt role focuses on building and maintaining ML infrastructure, deployment, and governance for production models in a healthcare setting.

You will collaborate with data scientists, software engineers, and DevOps to automate retraining, monitor performance, and ensure security/compliance of ML workflows.