GPU Compute Infra Engineer for ML Systems

Emploive; Greater London; Hybrid; GBP 100,000 - 180,000; Full time

Job summary

Emploive is seeking an experienced Infrastructure engineer to own the GPU compute powering our model training, evaluation, and serving systems. You’ll run Kubernetes clusters for GPU workloads, manage capacity with cloud providers, and collaborate across research, product, and platform teams.

This hybrid role in London/Paris involves monitoring reliability, improving scheduling, and diagnosing GPU/OS issues to deliver continuous improvements to the GPU stack.

Qualifications

• Have built and run GPU workloads on Kubernetes.
• Could design a GPU cluster for training and online RL from scratch.
• Debug confidently at the OS layer and below (Linux, GPU drivers, networking and storage).
• Write strong Python.

Responsibilities

• Running Kubernetes clusters for GPU training and inference
• Improving how GPU work is scheduled and placed
• Detecting, draining and repairing unhealthy GPU nodes
• Managing capacity with our cloud providers
• Debugging failures in GPUs, Linux, storage and networking

Skills

GPU workloads

Kubernetes

Python

Slurm

Kueue

Karpenter

SkyPilot

AWS EKS

SageMaker HyperPod

NCCL

Open MPI

Terraform

Linux

Job description

Emploive is seeking an experienced Infrastructure engineer to own the GPU compute powering our model training, evaluation, and serving systems. You’ll run Kubernetes clusters for GPU workloads, manage capacity with cloud providers, and collaborate across research, product, and platform teams.

This hybrid role in London/Paris involves monitoring reliability, improving scheduling, and diagnosing GPU/OS issues to deliver continuous improvements to the GPU stack.