Senior Kubernetes Platform Engineer (GPU & AI Infrastructure)

gtn technical staffing • Dallas-fort Worth Metroplex

Relocation

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AI Summary

Design and develop Kubernetes-native software to build a next-generation GPU-accelerated compute platform for AI, ML, and HPC workloads. Focus on custom operators, controllers, CRDs, and GPU scheduling while extending Kubernetes capabilities. Requires deep expertise in Kubernetes internals, Go/Python, and GPU infrastructure.

Key Highlights

Build Kubernetes-native software (operators, controllers, CRDs) for GPU-accelerated AI/ML/HPC workloads

Extend Kubernetes to support GPU scheduling, resource allocation, and high-performance networking

Integrate NVIDIA technologies (GPU Operator, MIG, DCGM) and develop internal tools for GPU management

Key Responsibilities

Develop Kubernetes-native software (custom operators, controllers, CRDs, APIs) to orchestrate GPU infrastructure

Extend Kubernetes to support GPU-intensive AI/ML and HPC workloads with scheduling, allocation, and resource isolation

Integrate NVIDIA technologies (GPU Operator, device plugins, MIG, DCGM) and build GPU scheduling capabilities

Automate cluster provisioning, lifecycle management, and infrastructure orchestration for GPU workloads

Develop internal tools and APIs for provisioning and managing GPU compute resources

Improve platform scalability, GPU utilization, workload performance, and reliability

Integrate Kubernetes with high-performance networking (InfiniBand, RDMA, RoCE) and bare-metal infrastructure

Build observability and automated remediation capabilities for distributed GPU environments

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Technical Skills Required

Kubernetes (operators, controllers, CRDs, scheduling, RBAC) Go GPU Infrastructure (NVIDIA technologies, Slurm, Volcano, CUDA, NCCL)

Benefits & Perks

Relocation assistance available

Hybrid work arrangement (3 days onsite, 2 days remote)

Full remote may be considered for exceptional candidates

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Nice to Have

Experience with Slurm, Volcano, or custom kube-scheduler extensions

Familiarity with CUDA, NCCL, PyTorch, or TensorFlow

Experience with InfiniBand, RDMA, or RoCE

Background in AI infrastructure, HPC, or large-scale distributed systems

Experience with bare-metal Kubernetes or internal developer platforms

Job Description

Senior Kubernetes Platform Developer – GPU & AI Infrastructure

Location: Dallas, TX preferred

Work Arrangement: Hybrid, 3 days onsite / 2 days remote

Remote Flexibility: Full remote may be considered for the right candidate

Relocation: Available

Employment Type: Direct Hire

Overview

We are seeking a Senior Kubernetes Platform Developer to design and build the software powering a next-generation GPU-accelerated compute platform supporting AI, machine learning, LLM, and HPC workloads.

This is a software development role focused on Kubernetes, not a traditional DevOps, SRE, or Kubernetes administration position.

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