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