Senior Systems Architect & MLOps Lead (Remote)

University of Miami; Miami (FL); Hybrid; USD 150.000 - 190.000; Vollzeit

Zusammenfassung

The University of Miami Health System is seeking a Systems Architect 2, MLOps Engineer to design, develop, and deploy clinical applications and ML platforms. You will lead the end‑to‑end lifecycle from concept to production, aligning with healthcare workflows and regulatory needs.

You will design scalable ML/AI infrastructure, manage hybrid cloud/on‑prem environments, and build robust CI/CD pipelines while collaborating with clinicians, data scientists, and IT teams.

Qualifikationen

• Bachelor's degree in a related field.
• 8+ years in systems architecture, DevOps, or MLOps.
• Experience with hybrid cloud/on-prem environments, Azure preferred.
• Healthcare or academic setting experience preferred.
• Mentoring and leading data teams or software eng teams.

Aufgaben

• Architect and implement infrastructure to support ML/AI workloads in clinical, research, and operational domains.
• Build and maintain CI/CD pipelines for automated ML model deployment, monitoring, and retraining.
• Collaborate with data scientists, IT teams, and clinical stakeholders to production‑ize models.
• Lead high‑complexity application implementations and project execution.
• Ensure governance, data privacy, and compliance across systems.

Kenntnisse

Python

Machine Learning

Leadership

Project governance

Independent work

Healthcare domain understanding

Ausbildung

Bachelor's Degree in relevant field

Tools

Docker

Kubernetes

Terraform

ARM templates

GitHub Actions

Jenkins

Azure DevOps

MLflow

DVC

Airflow

FHIR

HL7

DICOM

Jobbeschreibung

The University of Miami Health System is seeking a Systems Architect 2, MLOps Engineer to design, develop, and deploy clinical applications and ML platforms. You will lead the end‑to‑end lifecycle from concept to production, aligning with healthcare workflows and regulatory needs.

You will design scalable ML/AI infrastructure, manage hybrid cloud/on‑prem environments, and build robust CI/CD pipelines while collaborating with clinicians, data scientists, and IT teams.