Machine Learning (ML) Ops Engineer (AI/ML)

TL;DR

Machine Learning (ML) Ops Engineer (AI/ML): Design, build, and maintain production-grade machine learning models and infrastructure for clinical research applications with an accent on scalability, real-time inference, and integration with healthcare data. Focus on developing end-to-end ML pipelines, monitoring for data drift, automating retraining, and optimizing CI/CD deployments using cloud platforms like AWS, GCP, or Azure.

Location: Los Angeles, CA - Health Sciences Campus (onsite full-time). Required Fire Life Safety Training (LA City).

Salary: $145,600 - $240,240 annually.

Company

Leading medical institution advancing clinical research through AI solutions at hirify.global.

What you will do

• Design, build, and maintain production-grade ML models with real-time inference, scalability, and reliability.
• Develop scalable ML infrastructure and AI pipelines using AWS, GCP, or Azure for data ingestion, preprocessing, and retrieval.
• Monitor model performance for data and concept drift, automate retraining to ensure accuracy.
• Implement CI/CD pipelines, containerization with Docker/Kubernetes, and version control for ML models.
• Configure monitoring, logging, and ensure security/compliance for AI systems.
• Collaborate with data scientists, engineers, and clinical teams to deploy and improve ML solutions.

Requirements

• Bachelor’s degree in computer science, engineering, or related field.
• Proven experience with AI/ML platforms (AWS, Azure, GCP), Docker/Kubernetes, CI/CD (Github Actions), Python/R/SQL, MLOps principles, and healthcare data use cases.
• Deep understanding of coding, architecture, deployment, and problem-solving through troubleshooting.
• Strong analytical, organizational skills, and ability to handle vague requirements as a self-starter.
• Fire Life Safety Training (LA City) required within 30 days of hire.

Nice to have

• Master’s degree in computer science, engineering, or related field.

Culture & Benefits

• Full-time exempt position with comprehensive university benefits.
• Equal opportunity employer committed to diversity and accommodations for disabilities.
• Background screening per USC policy, considering fair chance hiring.