Systems Architect 2, MLOps Engineer

What you'll do

• Design and deploy clinical applications and technologies based on user needs, cost, and system integration requirements.
• Architect and implement infrastructure to support machine learning and artificial intelligence workloads across research and clinical domains.
• Build and maintain CI/CD pipelines for automated ML model deployment, monitoring, and retraining using tools like GitHub Actions or Jenkins.
• Utilize Python and machine learning frameworks to build scalable platforms for reproducible ML/AI solutions.
• Manage hybrid cloud and on-premises environments to ensure high-performance computing and HIPAA compliance.
• Design and implement robust APIs to integrate ML models with internal and external clinical systems.
• Monitor system performance, model drift, and data integrity in real-time to maintain the reliability of deployed models.
• Lead high-complexity projects by defining requirements, managing vendor relationships, and mentoring senior analysts.

What we're looking for

• Bachelor's Degree in a relevant field.
• Minimum 8 years of experience in systems architecture, DevOps, or MLOps.
• Strong proficiency in Python and machine learning frameworks like TensorFlow or PyTorch.
• Strong proficiency with containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, ARM templates).
• Proficiency with CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps.
• Experience deploying and maintaining production workloads and major systems development and implementation.
• Experience with hybrid cloud/on-prem environments, Azure preferred.
• Epic or Healthcare EMR certification preferred.