Remote Kubernetes Platform Engineer for AI/ML & HPC

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

Benefits offered by this job

Paid time off

Medical coverage

Retirement savings

Life and disability insurance

Employee assistance programs

Job summary

Capgemini Engineering, a leader in engineering services, seeks an experienced Kubernetes/HPC Engineer to design, deploy, and support scalable compute platforms for AI/ML and simulations. The role is remote-based in the USA, offering exposure to cloud and on-prem environments and a opportunity to influence high-performance workloads.

You will build CI/CD pipelines, automate infrastructure, and optimize performance across distributed systems, using Kubernetes, Docker, Helm, and GPU infrastructure.

Qualifications

• 5+ years of experience in Kubernetes, Platform Engineering, Cloud Infrastructure, DevOps, or SRE.
• 2+ years supporting HPC environments or large compute clusters.
• Hands-on expertise with Kubernetes, Docker, Helm.
• Experience with HPC schedulers like Slurm or Volcano.
• Experience with NVIDIA GPU infrastructure and AI/ML workloads.

Responsibilities

• Design, deploy, and manage Kubernetes-based platforms supporting AI/ML and HPC.
• Build and optimize HPC environments with workload schedulers.
• Deploy and support NVIDIA GPU infrastructure for ML workloads.
• Implement CI/CD pipelines and Infrastructure-as-Code practices.
• Manage containerized apps using Kubernetes, Docker, Helm, and cloud-native tech.
• Troubleshoot and optimize performance across distributed computing environments.

Skills

Kubernetes

Platform Engineering

Cloud Infrastructure

DevOps

Site Reliability Engineering

HPC environments

Tools

Docker

Helm

Slurm

Volcano

Terraform

Job description

Capgemini Engineering, a leader in engineering services, seeks an experienced Kubernetes/HPC Engineer to design, deploy, and support scalable compute platforms for AI/ML and simulations. The role is remote-based in the USA, offering exposure to cloud and on-prem environments and a opportunity to influence high-performance workloads.

You will build CI/CD pipelines, automate infrastructure, and optimize performance across distributed systems, using Kubernetes, Docker, Helm, and GPU infrastructure.