Systems Architect 2, MLOps Engineer
Core
Design, develop, and deploy clinical applications and technologies; architect infrastructure for ML/AI workloads across research, clinical, and operational domains.
Role type
Senior Systems Architect / MLOps Engineer
Builds
Production-ready ML/AI services, scalable infrastructure, and integrated clinical applications
Domain
Healthcare IT / Machine Learning Operations
Deliverable
production ML models
Required skills
Systems architecture, MLOps, Python, ML frameworks (TensorFlow, PyTorch), containerization (Docker), orchestration (Kubernetes), infrastructure-as-code (Terraform), CI/CD pipelines, API design (RESTful, gRPC), healthcare data standards (FHIR, OMOP, DICOM), project management, vendor management
Preferred skills
Epic/Healthcare EMR certification, healthcare or academic settings experience, mentoring data teams, high-performance computing (HPC) or GPU workloads, responsible AI practices
Technologies
Python, TensorFlow, PyTorch, Docker, Kubernetes, Terraform, GitHub Actions, Jenkins, Azure DevOps, MLflow, DVC, Airflow, Azure, RESTful, gRPC, FHIR, HL7, DICOM
Responsibilities
Engineer new workflows optimizing business processes; lead high-complexity application implementation projects; analyze current systems to recommend enhancements; mentor senior analysts; manage vendor relationships and contract negotiations; resolve complex integration problems; implement MLOps frameworks for model governance and versioning; design APIs to serve ML models; monitor model drift and data integrity; collaborate with stakeholders to translate models into production services.
Seniority
Senior, hands-on IC with leadership responsibilities
