C

Capgemini

Global consulting, technology services, outsourcing

Kubernetes - K8S, / HPC Engineer

Platform EngineeringUpdated on Nov 14
Full-timeRemote in USA

About the Job

Requirements

  • At least 5 years of experience in Kubernetes, platform engineering, cloud infrastructure, DevOps, Site Reliability Engineering, or related technical disciplines.
  • At least 2 years of experience supporting High-Performance Computing environments, distributed computing platforms, or large-scale compute clusters.
  • Hands-on expertise with Kubernetes, Docker, Helm, and container orchestration technologies.
  • Experience managing HPC clusters and workload schedulers, including Slurm, Volcano, or similar scheduling platforms.
  • Expertise with NVIDIA GPU infrastructure, GPU-enabled workloads, performance optimization, and accelerated computing environments.
  • Linux administration, troubleshooting, and automation skills, including Python and Bash scripting.
  • Experience implementing CI/CD pipelines, monitoring, logging, observability, and infrastructure automation solutions.
  • Hands-on experience with major cloud platforms, including Azure Kubernetes Service, Google Kubernetes Engine, or comparable cloud-native services.
  • Understanding of distributed systems, cloud-native architectures, scalability, reliability, and performance tuning.

Responsibilities

  • Design, deploy, and manage Kubernetes-based platforms supporting AI/ML, HPC, and distributed computing workloads.
  • Build, administer, and optimize HPC environments using workload schedulers such as Slurm and Volcano.
  • Deploy and support NVIDIA GPU infrastructure for machine learning, simulation, and accelerated computing workloads.
  • Implement infrastructure automation, CI/CD pipelines, and Infrastructure-as-Code practices to improve platform scalability and operational efficiency.
  • Manage containerized applications using Kubernetes, Docker, Helm, and cloud-native technologies.
  • Troubleshoot and optimize cluster, network, storage, and application performance across distributed computing environments.

Desired Qualifications

  • Experience supporting AI/ML platforms and large-scale model training workloads.
  • Exposure to AWS Trainium, AWS Inferentia, or AI accelerator technologies.
  • Experience with Infrastructure-as-Code tools such as Terraform.
  • Knowledge of cloud networking, storage systems, and hybrid cloud architectures.
  • Experience with observability platforms such as Prometheus and Grafana.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

Recently Posted Jobs

Explore more opportunities at Capgemini

See more jobs