Senior DevOps / MLOps Engineer
Tasks
- Build machine learning pipelines
- Deploy machine learning models
- Enforce cybersecurity policies
- Implement CI/CD integrations
- Implement infrastructure logging
- Implement infrastructure monitoring
- Integrate Kubeflow
- Integrate Ray
- Maintain automated machine learning pipelines
- Manage Kubernetes infrastructure
- Manage machine learning model lifecycles
- Optimize infrastructure performance
- Scale infrastructure services
- Schedule GPU resources
- Support Gitlab
- Support Google Workspace
- Support distributed training
- Troubleshoot hardware issues
- Troubleshoot network issues
- Troubleshoot software issues
Perks/Benefits
- N/A
Skills/Tech-stack
CI/CD | Cybersecurity | DVC | Data version control | Distributed Training | GPU scheduling | GitLab | Google Workspace | Kubeflow | Kubernetes | Lifecycle Management | Logging | MLOps | Machine Learning | Machine Learning Pipelines | Model Lifecycle | Model Lifecycle Management | Model Serving | Monitoring | Ray | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Regions
Countries
States
Cities
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