Remote Kubernetes & HPC Engineer – AI/ML Infra

Capgemini; Atlanta (GA); Remote; USD 77,000 - 151,000; Full time

Benefits offered by this job

401(k) match

Medical, dental, vision coverage

Paid time off

Job summary

Capgemini is seeking a Kubernetes (K8S) / HPC Engineer to design, deploy, and support scalable compute platforms powering AI/ML, simulation, and compute-intensive workloads. You will work with platform engineering, data science, and research teams to deliver high-performance infrastructure across cloud and on-premises environments.

The role emphasizes automation, CI/CD, and container orchestration, with exposure to NVIDIA GPU infrastructure and Slurm/Volcano schedulers.

Qualifications

• 5+ years of experience in Kubernetes, Cloud Infrastructure, Platform Engineering, DevOps, or related fields.
• Minimum 2+ years of experience supporting HPC or large-scale distributed compute environments.
• Strong hands-on experience with Kubernetes (K8S), Docker, Helm, and container orchestration technologies.
• Exposure to Trainium or Inferentia is highly preferred.
• Experience managing HPC clusters and workload schedulers, including Slurm and/or Volcano.
• Expertise with NVIDIA GPU infrastructure, GPU-enabled workloads, and performance optimization.
• Strong Linux administration and troubleshooting skills.
• Proficiency in Python and/or Bash scripting for automation and operational management.
• Experience implementing CI/CD pipelines, monitoring, logging, and infrastructure automation solutions.
• Hands-on experience with Azure AKS and Google Kubernetes Engine (GKE).
• Strong understanding of distributed systems, cloud-native architectures, scalability, and performance tuning.

Responsibilities

• Design, deploy, and manage Kubernetes-based compute platforms for AI/ML and HPC workloads.
• Build and maintain scalable HPC environments utilizing workload schedulers.
• Support and optimize NVIDIA GPU infrastructure for machine learning, data processing, and simulation workloads.
• Implement infrastructure automation, CI/CD pipelines, and monitoring solutions.
• Manage containerized applications using Kubernetes, Docker, and Helm.
• Troubleshoot and optimize cluster, network, storage, and application performance across distributed computing environments.
• Collaborate with engineering, research, and AI teams to enable high-performance computing and cloud-native solutions.
• Ensure platform scalability, availability, security, and operational excellence.

Skills

Kubernetes

Docker

Helm

Cloud Infrastructure

Platform Engineering

DevOps

NVIDIA GPU

Python

Bash scripting

CI/CD pipelines

Azure AKS

GKE

Slurm

Volcano

Linux

Distributed systems

Tools

Docker

Kubernetes

Job description

Capgemini is seeking a Kubernetes (K8S) / HPC Engineer to design, deploy, and support scalable compute platforms powering AI/ML, simulation, and compute-intensive workloads. You will work with platform engineering, data science, and research teams to deliver high-performance infrastructure across cloud and on-premises environments.

The role emphasizes automation, CI/CD, and container orchestration, with exposure to NVIDIA GPU infrastructure and Slurm/Volcano schedulers.