Senior Kubernetes Engineer – GPU-Accelerated Compute Platform (Go/Python)

gtn technical staffing • Dallas-fort Worth Metroplex

Relocation

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AI Summary

Design and develop Kubernetes-native software to power a next-gen GPU-accelerated compute platform for AI, ML, LLM, and HPC workloads. Focus on building custom operators, controllers, CRDs, and GPU scheduling solutions while extending Kubernetes for high-performance distributed systems. 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 to support GPU scheduling, resource isolation, and high-performance networking

Collaborate with NVIDIA technologies (GPU Operator, MIG, DCGM) and integrate with Slurm/Volcano-like schedulers

Key Responsibilities

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

Extend Kubernetes to support GPU-intensive AI/ML and HPC workloads with custom schedulers and resource isolation

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

Integrate NVIDIA technologies (GPU Operator, device plugins, MIG, DCGM) and high-performance networking (InfiniBand, RDMA)

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

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

Build observability and automated remediation capabilities for distributed compute environments

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Technical Skills Required

Kubernetes (operators, controllers, CRDs, scheduling, RBAC, networking) Go GPU infrastructure (NVIDIA technologies, CUDA, high-performance networking)

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

NVIDIA GPU clusters

Slurm, Volcano, or custom Kubernetes schedulers

CUDA, NCCL, PyTorch, or TensorFlow

InfiniBand, RDMA, RoCE

Bare-metal Kubernetes

AI infrastructure, HPC, or large-scale distributed systems experience

Job Description

Senior Software Engineer – Kubernetes Operators & Controllers

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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