Machine Learning (ML) Ops Engineer - IS Clinical Research - Full Time 8 Hour Days (Exempt) (Non-Union)

Position Overview

Under the direction of Information Services Leadership, the incumbent will be responsible for the full lifecycle management of machine learning models – from design and build to maintenance. The MLOps Engineer will implement artificial intelligence solutions at Keck Medicine of USC by partnering with data scientists, clinical operations, and DevOps teams to deploy, monitor, and maintain ML models that improve patient care, support operational excellence, and advance clinical research. They will ensure seamless integration, automation, and scaling of AI solutions leveraging best practices in testing, debugging and performance monitoring.

Key Responsibilities

• Design, build, and maintain production-grade machine learning models with real-time inference, scalability, and reliability.
• Develop end-to-end scalable ML infrastructure using cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
• Create AI pipelines for data ingestion, pre-processing, and search and retrieval to meet technical and business requirements.
• Monitor model performance for data drift, automate retraining processes, and maintain model accuracy and relevance.
• Collaborate with data scientists, engineers, analytics, and DevOps teams to design and implement robust deployment pipelines.
• Implement and optimize CI/CD pipelines for automating testing and deployment of machine learning models.
• Configure and manage monitoring and logging solutions to track system health, model performance, and anomalies.
• Implement version control for models, parameters, results, and associated code to facilitate collaboration.
• Ensure all machine learning systems comply with security and privacy regulations.
• Lead efforts in developing methods for ML/GenAI model engineering, advancing LLMs, and optimizing deployment frameworks in line with strategic goals.
• Maintain clear and comprehensive documentation of MLOps processes and configurations.
• Collaborate cross-functionally to align on deployment strategies and technical requirements.
• Perform other duties as assigned.

Required Qualifications

• Bachelor's Degree in computer science, engineering, or a closely related field.
• Proven experience with artificial intelligence and machine learning platforms (e.g., AWS, Azure, or GCP); containerization technologies (e.g., Docker) and orchestration platforms (e.g., Kubernetes); CI/CD tools (e.g., Github Actions); programming languages and frameworks (e.g., Python, R, SQL); MLOps engineering principles; agile methodologies; and DevOps lifecycle management. Experience with technical writing and documentation for AI/ML models and processes is also required.
• Ability to solve complex problems through effective troubleshooting.
• Deep understanding of coding, architecture, and deployment processes.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate large amounts of information with attention to detail and accuracy.
• Excellent organizational skills and meticulous attention to detail.
• Self-starter with the ability to develop solutions when requirements are vague or ambiguous.
• Fire Life Safety Training (LA City) – if not already certified, one must be obtained within 30 days of hire and maintained thereafter (required within LA City only).

Preferred Qualifications

• Master's Degree in computer science, engineering, or a closely related field.

Benefits & Perks

• Compensation: $145,600.00 - $240,240.00

Quick Apply

Apply here: https://usccareers.usc.edu/job/-/-/1209/80041515552