Senior Kubernetes Engineer

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. 26-00812