Senior Kubernetes Platform Engineer - AI/ML Infrastructure
Research Triangle Park, North Carolina, United States of America
R
USD 139K-203K Senior-level Full Time
Tasks
- Architect Kubernetes platform
- Automate platform operations
- Build Kubernetes controllers
- Build Kubernetes operators
- Build Kubernetes platforms
- Contribute to best practices
- Create CRDs
- Define platform engineering standards
- Deploy LLM workloads on Kubernetes
- Develop Golang services
- Develop multi tenant platform architecture
- Drive reliability automation
- Enable ML inference on Kubernetes
- Enable ML training on Kubernetes
- Implement AIOps telemetry
- Implement infrastructure-as-code
- Implement self-healing systems
- Improve observability logs
- Improve observability metrics
- Improve observability traces
- Maintain cluster performance
- Manage Kubernetes control plane
- Manage etcd lifecycle
- Mentor engineers
- Operate Kubernetes platforms
- Operationalize ML workflows
- Optimize resource utilization
- Optimize scheduling
- Perform anomaly detection
- Provide production incident response
Perks/Benefits
- 401k plan
- Basic life insurance
- Life insurance
- Long-term disability
- Medical/Dental/Vision insurance
- On-site work flexibility
- Paid Holidays
- Paid parental leave
- Paid time off
- Short-term disability
Skills/Tech-stack
AIOps | Anomaly Detection | Anthos | CRD | Control Plane | Deep learning | Distributed Systems | Etcd | GPU Workloads | Golang | Incident Management | Infrastructure as Code | Kubernetes | Kubernetes Operators | Kubernetes controllers | LLM | Logging | Machine Learning | Metrics | Multi-tenant | Multi-tenant architecture | Observability | On-Call | On-call incident management | OpenShift | Resource utilization | Scheduling | Self-healing | Telemetry | Tenant architecture | Tracing | Webhooks | “as-code”
Education
N/A
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