GPU Compute Infra Engineer: Kubernetes & Multi-Cloud

Hcompany; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Competitive package

Job summary

Hcompany is building a globally distributed GPU compute platform to power model training, evaluation, and serving. This hybrid role sits in the Platform Infrastructure team, managing clusters, GPUs, and schedulers and optimizing capacity across cloud providers.

You will run Kubernetes clusters for GPU training and inference, improve scheduling, and handle node health and repair. Strong Python skills and experience with GPU tooling are essential for success.

Qualifications

• Built and run GPU workloads on Kubernetes.
• Able to design a GPU cluster for training and online RL from scratch.
• Debug confidently at the OS layer (Linux, GPU drivers, networking, storage).
• Strong Python programming skills.

Responsibilities

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

Skills

GPU workloads

Kubernetes

Python

OS debugging

Tools

Slurm

Kueue

Karpenter

Terraform

SkyPilot

Job description

Hcompany is building a globally distributed GPU compute platform to power model training, evaluation, and serving. This hybrid role sits in the Platform Infrastructure team, managing clusters, GPUs, and schedulers and optimizing capacity across cloud providers.

You will run Kubernetes clusters for GPU training and inference, improve scheduling, and handle node health and repair. Strong Python skills and experience with GPU tooling are essential for success.