MD.ai helps doctors, scientists, and engineers build medical AI that have potential to improve patient care and outcomes. We provide software tools to enable large-scale collaborative dataset curation and annotation as well as model deployment and federated clinical validation, with a particular focus on medical imaging.
As as Lead Infrastructure Engineer, you will drive development of our core product's underlying technical cloud infrastructure, and establish automated deployment processes serving multiple cloud environments (GCP, AWS, Azure), including managing our customer's unique deployment and security requirements. We use Kubernetes and Terraform for infrastructure management. Many of our platform services require elastic scaling, including data ingestion/processing and ML model serving (involving GPUs).
What you will do
- Architect and build core infrastructure components and processes for enterprise deployments
- Ensure uptime and reliability of services
- Improve deployment process automation
- Implement and maintain security policies
- Assist with technical documentation
- Collaborate with other team members to establish and enable development best practices
- Help build and develop engineering and team culture
What you should have
- 3+ years of cloud infrastructure engineering or similar experience
- Demonstrated knowledge and proficiency with GCP, AWS, and Azure
- Experience with deployments using Docker, Kubernetes, and Terraform
- Knowledge of HIPAA, GDPR, SOC 2
- Experience with ML model development
- Familiarity with git workflows and CI/CD practices
- Knowledge of healthcare and medical imaging IT systems
MD.ai is an equal opportunity employer that is committed to diversity and inclusion. We do not discriminate based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other legally protected characteristics.
