Senior Kubernetes Engineer (GPU-Accelerated AI/ML Platform)

gtn technical staffing • Dallas-fort Worth Metroplex

Relocation

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AI Summary

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

Key Highlights

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

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

Strong software development focus—no DevOps/SRE administration experience preferred

Key Responsibilities

Develop Kubernetes-native software (custom operators, controllers, CRDs, APIs) using Go or Python

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

Integrate NVIDIA technologies (GPU Operator, device plugins, MIG, DCGM) into the platform

Build automation for cluster provisioning, lifecycle management, and GPU resource orchestration

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

Develop internal tools and APIs for GPU compute resource provisioning and management

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

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Technical Skills Required

Kubernetes Go GPU Infrastructure (NVIDIA Technologies)

Benefits & Perks

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

Relocation assistance available for qualified non-local candidates

Full remote work may be considered for exceptional candidates

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Nice to Have

Experience with NVIDIA GPU clusters

Slurm, Volcano, or custom Kubernetes scheduling solutions

CUDA, NCCL, PyTorch, or TensorFlow

Bare-metal Kubernetes deployments

AI infrastructure, HPC, or large-scale distributed systems

Job Description

Senior Kubernetes Engineer

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 for qualified non-local candidates

Employment Type: Direct Hire

Overview

Our client is seeking a Senior Kubernetes Engineer 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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