Machine Learning Engineer (MLOps / AI Infrastructure)

Prosum is a leading healthcare organization focused on AI-driven patient care and operational innovation. They are seeking a Machine Learning Engineer to design and deploy AI solutions that enhance patient outcomes and healthcare delivery in a mission-critical environment.

Responsibilities:

• Own the end-to-end ML lifecycle (build → deploy → monitor → scale)
• Design and maintain production-grade ML systems with real-time inference
• Build and optimize CI/CD pipelines for machine learning workflows
• Develop scalable ML infrastructure in cloud environments (AWS, Azure, or GCP)
• Implement monitoring, logging, and performance tracking for deployed models
• Partner cross-functionally with data scientists, engineers, and clinical teams
• Support GenAI/LLM deployments, including RAG-based systems

Requirements:

• MUST HAVE HEALTHCARE PROVIDER EXPERIENCE, do not submit yourself without it
• 3+ years in Machine Learning Engineering / MLOps / ML Infrastructure
• Proven experience managing end-to-end ML lifecycle in production
• Strong hands-on experience with: Python (will be tested live in interview)
• Docker + Kubernetes
• Terraform (required)
• CI/CD tools (GitHub Actions preferred)
• Experience with cloud platforms (AWS, Azure, or GCP)
• Deep understanding of: System architecture
• Deployment pipelines
• Performance optimization
• Experience with: LLMs, NLP, and predictive modeling
• RAG frameworks (must be able to explain and implement)
• Experience working with healthcare data
• Familiarity with: EHR systems
• Data privacy / compliance standards
• Preference: Southern California but will take candidates located in PDT, MST, and CST
• GitHub Actions preferred