Key skills
Machine LearningAI PlatformMLOpsAWSAzureDockerKubernetesInfrastructure as CodePythonAI TestingAI MonitoringHIPAAFERPAAWS Machine LearningAzure AI-102Kubernetes Certified Administrator (CKA)AIMLCI/CD
About this role
Huron is redefining what a global consulting organization can be. As a Platform Engineer in the AI Capability Center Hub, you will build and run the platform used by various pods, focusing on pipelines, testing, deployment, and monitoring.
Responsibilities:
- Build and run the pipelines. CI/CD with automated testing across the pods
- Provision the environments. Set up and run the environments the pods build in
- Deploy and monitor. The models and agents the pods put into production
- Set the standards. Technical and security standards every pod builds to
- Build reusable parts. So each new pod starts further ahead than the last
Requirements:
- 5 to 8 years in ML or AI platform work or MLOps, including 1 to 2 years leading
- Hands-on running AI systems in production
- AWS and Azure, Docker, Kubernetes, infrastructure as code
- Strong Python
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience
- Building internal developer platforms
- AI testing and monitoring in production
- Healthcare or higher education with data-security awareness (HIPAA, FERPA)
- AWS Machine Learning or DevOps, Azure AI-102, or Kubernetes (CKA)