Machine Learning Engineer 4
Tasks
- Analyze resource usage
- Apply Kubernetes security measures
- Architect Kubernetes clusters
- Build Kubernetes provisioning automation
- Collaborate on application integration
- Configure pod scheduling
- Deploy Kubernetes clusters
- Document processes and configurations
- Ensure compliance standards
- Forecast capacity requirements
- Implement alerting mechanisms
- Implement disaster recovery strategies
- Implement scaling
- Maintain Kubernetes clusters
- Maintain infrastructure-as-code
- Manage containerized applications
- Mentor junior team members
- Optimize performance bottlenecks
- Perform rolling deployments
- Provide Kubernetes training
- Set up monitoring tools
- Support Kubernetes application deployment
- Troubleshoot Kubernetes infrastructure
- Troubleshoot application deployments
- Troubleshoot networking
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Alerting | Artificial Intelligence | Automation | Autoscaling | Capacity Planning | Containerization | Disaster Recovery | Infrastructure as Code | Java | Kubernetes | Machine Learning | Monitoring | Networking | Performance optimization | Pod Scheduling | Python | Resource Management | Rolling deployments | Security | Shell Scripting | TensorFlow | “as-code”
Education
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