Senior Kubernetes Engineer for GPU-Accelerated AI/HPC

Devopsroles; Dallas (TX); Presencial; USD 140.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Lunch stipend

Company-paid medical

Dental and Vision benefits

16 weeks parental leave

401(k) matching

Flexible benefits

Descripción de la vacante

NorthMark Compute & Cloud (NMC²) in Dallas seeks a Senior Kubernetes Engineer to design and operate GPU-accelerated container platforms at scale for AI/ML, HPC, and data-intensive workloads across hybrid or on-prem environments.

You will work with NVIDIA and Kubernetes ecosystems, implement custom operators, improve scheduling, and integrate observability and security controls. Collaboration with HPC/ML/DevOps teams is essential to ensure high-throughput and multi-tenant performance.

Formación

• Extensive production-grade Kubernetes experience with GPU workloads.
• Experience with NVIDIA GPU Operator, MIG, and DCGM.
• Proficient in Go or Python for operators.
• Strong understanding of RBAC, namespaces and policy enforcement.
• Experience with GitOps pipelines (ArgoCD/FluxCD).

Responsabilidades

• Architect Kubernetes clusters for GPU workloads using NVIDIA tools.
• Develop and maintain custom Kubernetes operators and controllers.
• Integrate NVIDIA device plugins and MIG into scheduling layer.
• Optimize GPU utilization with scheduler extensions and Slurm/Volcano.
• Collaborate with HPC/ML/DevOps teams for multi-tenant performance.
• Drive observability with Prometheus, Grafana, DCGM Exporter, OpenTelemetry.
• Maintain CI/CD pipelines for infrastructure with GitOps (ArgoCD/FluxCD) and Terraform.
• Contribute to IaC using Terraform, Helm, and Kustomize.
• Participate in performance tuning and production readiness reviews.

Conocimientos

Kubernetes

NVIDIA GPUs

Go or Python

RBAC & security

GitOps

Prometheus/Grafana

DCGM

Herramientas

NVIDIA GPU Operator

Helm

Kustomize

ArgoCD

FluxCD

Terraform

Descripción del empleo

NorthMark Compute & Cloud (NMC²) in Dallas seeks a Senior Kubernetes Engineer to design and operate GPU-accelerated container platforms at scale for AI/ML, HPC, and data-intensive workloads across hybrid or on-prem environments.

You will work with NVIDIA and Kubernetes ecosystems, implement custom operators, improve scheduling, and integrate observability and security controls. Collaboration with HPC/ML/DevOps teams is essential to ensure high-throughput and multi-tenant performance.