ML GPU Infra Engineer: Kubernetes, Scheduling & Hybrid

H Company; Paris; Hybrid; EUR 90,000 - 150,000; Full time

Job summary

H Company is looking for a Senior Infrastructure Engineer to own GPU compute powering model training, evaluation, and serving systems. You’ll operate clusters from Kubernetes to GPU hardware, coordinating capacity with cloud providers.

You will improve GPU scheduling, detect and repair unhealthy nodes, and scale a globally distributed GPU system over time. Collaboration with Platform Infrastructure, research, and product teams is essential.

Qualifications

• Experience running GPU workloads on Kubernetes.
• Ability to design GPU clusters for training and online RL.
• Deep debugging skills at OS level (Linux) and below.

Responsibilities

• Run Kubernetes clusters for GPU training and inference.
• Improve scheduling and placement of GPU work.
• Detect, drain and repair unhealthy GPU nodes.
• Manage capacity with cloud providers.
• Debug GPU, Linux, storage and networking failures.

Skills

GPU on Kubernetes

GPU cluster design

OS debugging

Python

Tools

Slurm

Kueue

Karpenter

SkyPilot

AWS EKS

SageMaker HyperPod

Terraform

Job description

H Company is looking for a Senior Infrastructure Engineer to own GPU compute powering model training, evaluation, and serving systems. You’ll operate clusters from Kubernetes to GPU hardware, coordinating capacity with cloud providers.

You will improve GPU scheduling, detect and repair unhealthy nodes, and scale a globally distributed GPU system over time. Collaboration with Platform Infrastructure, research, and product teams is essential.