Senior Kubernetes Platform Engineer - AI/ML Infrastructure
USD 139K-203K Senior-level Full Time
Tasks
- Architect build and operate on prem Kubernetes platforms
- Build Kubernetes controllers operators and CRDs
- Define multi tenant platform architecture for AI ML workloads
- Develop platform services in Go
- Drive AIOps with telemetry anomaly detection and self healing
- Enable and optimize ML training inference and LLM deployment pipelines
- Implement infrastructure-as-code for automation
- Improve observability with metrics, logs, and traces
- Manage Kubernetes control plane and etcd lifecycle
- Mentor engineers and define platform engineering standards
- Operate production incident response and reliability improvements
- Optimize scheduling and resource utilization
Perks/Benefits
- 401k plan with employer match
- Disability coverage
- Hybrid work option
- Paid Holidays
- Paid parental leave
- Paid time off
- Sick time
- Volunteer time off
Skills/Tech-stack
AIOps | Anomaly Detection | Custom Resource Definitions | Deployment Pipelines | Distributed Systems | Distributed tracing | Etcd | GPU | Go | Google Anthos | Incident Response | Infrastructure as Code | Kubernetes | Kubernetes Operators | Kubernetes Webhooks | Kubernetes controllers | LLM Deployment | LLM Deployment Pipelines | Language Models | Large Language Models | Logging | Machine Learning | Metrics | Observability | OpenShift | Resource utilization | Scheduling | Telemetry | “as-code”
Education
N/A
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