Werkstudent MLOps-Plattform & Cloud-Native Infrastruktur
Tasks
- Automate deployment and build steps
- Build and maintain Docker images
- Deploy services using Helm Kustomize and Kubernetes manifests
- Develop and maintain infrastructure as code
- Develop unit, integration and end-to-end tests
- Implement and configure service interfaces for model inference protocols
- Integrate event streaming for inference logging
- Integrate services using REST GraphQL and message queues
- Integrate software infrastructure and ML components into a platform
- Maintain architecture deployment and runbook documentation
- Manage Kubernetes clusters and configurations
- Manage container images in a container registry
- Operate Kubeflow Pipelines and Training Operator
- Operate MLflow for experiment tracking and model registry
- Prepare demos presentations and reproducible materials
- Register deploy and version machine learning models
- Serve models using KServe
- Store artifacts using MinIO
- Troubleshoot Kubernetes pods services logs and events
Perks/Benefits
Skills/Tech-stack
CloudEvents | Docker | Git | GraphQL | Helm | KServe | Kafka | Kubectl | Kubeflow Pipelines | Kubeflow Training Operator | Kubernetes | Kustomize | Linux | MLflow | Message Queues | Minio | OpenStack | OpenTofu | PyTorch | Python | REST | Terraform
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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