Werkstudent MLOps-Plattform & Cloud-Native Infrastruktur
Tasks
- Build Docker images for services
- Build ML platform components
- Configure REST and GraphQL service interfaces
- Create and maintain CI/CD pipelines
- Debug cluster issues with kubectl
- Deploy services with Helm and Kustomize
- Develop infrastructure as code architecture
- Document architecture and runbooks
- Implement MLflow model tracking and registry
- Implement message queue integration
- Integrate event streaming for inference logging
- Manage container registry images
- Operate Kubeflow Pipelines and Training Operator
- Operate Kubernetes clusters
- Prepare demos and reproduction materials
- Register and deploy ML models
- Run training and serving pipelines
- Serve models with KServe
- Use MinIO for S3 compatible storage
- Write unit, integration, and end-to-end tests
Perks/Benefits
Skills/Tech-stack
CI/CD | CloudEvents | Docker | End to End | End-to-End Testing | Git | GraphQL | Helm | Helm Charts | Integration Testing | KServe | Kafka | Kafka Connect | Kubeconfig | Kubectl | Kubeflow | Kubeflow Pipelines | Kubernetes | Kustomize | Linux | MLflow | Markdown | Message Queues | Minio | OpenShift | OpenStack | OpenTofu | Python | REST | S3 | Smoke Testing | Terraform | Unit Testing
Education
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