As an ML Engineering Consultant at CBTW, I specialized in taking machine learning proof-of-concepts to production for healthcare clients.
What I Did
I worked across three major healthcare client projects, each requiring different approaches to operationalizing ML models. The common thread was taking research-grade models and building production-ready systems around them on Azure and Kubernetes infrastructure.
For each project, I designed and implemented ML backend web services that could handle healthcare data integration requirements. This involved working with various medical data formats, ensuring HIPAA-equivalent compliance for European healthcare data, and building robust APIs.
I took on significant stakeholder management responsibilities, regularly presenting project progress and milestones to C-Suite executives at client organizations. This required translating technical ML concepts into business value propositions.
Key Achievements
- •Successfully operationalized ML PoCs across 3 major healthcare projects
- •Built production ML systems on Azure + Kubernetes infrastructure
- •Designed compliant data models for medical data integration
- •Presented technical projects to C-Suite executives
- •Established MLOps practices in healthcare consulting engagements