Senior Kubernetes Engineer

This role involves designing, implementing, and optimizing GPU-accelerated container platforms for high-performance workloads such as AI/ML and HPC across hybrid or on-prem environments. Responsibilities: Architect and operate Kubernetes clusters optimized for GPU workloads.

Duration: 6+ months
Compensation: $100-120/hr W2
Location: Downtown Dallas
 
This role involves designing, implementing, and optimizing GPU-accelerated container platforms for high-performance workloads such as AI/ML and HPC across hybrid or on-prem environments. The position requires deep expertise in both NVIDIA and Kubernetes ecosystems.
 
Responsibilities:

• Architect and operate Kubernetes clusters optimized for GPU workloads.
• Develop and maintain custom Kubernetes operators and controllers.
• Integrate NVIDIA device plugins and optimize GPU utilization.
• Collaborate with HPC, ML, and DevOps teams for high-throughput cluster performance.
• Drive observability and telemetry integrations.
• Implement secure multi-user and multi-namespace GPU isolation.
• Maintain CI/CD pipelines for Kubernetes infrastructure.
• Contribute to infrastructure-as-code using tools like Terraform and Helm.
• Participate in performance tuning and incident response.

Requirements:

• Extensive experience with Kubernetes in production environments.
• Proficiency in Go or Python for operator development.
• Deep understanding of Kubernetes internals and GPU-intensive workloads.
• Hands-on experience with Helm, Kustomize, and GitOps workflows.
• Familiarity with CNI plugins, especially NVIDIA CNI and Multus.
• Experience with monitoring GPU metrics using Prometheus and DCGM Exporter.

 
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