MLOps & Infrastructure Engineer for Scalable AI Compute

graphcore; United Kingdom; Hybrid; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Flexible working

Private medical insurance

Pension (matched up to 5%)

Life assurance

Income protection

Parental leave

Employee assistance programme

Healthy snacks

Barista bar

Job summary

Graphcore in the United Kingdom is seeking a Software Infrastructure Engineer to scale and manage our infrastructure. You will develop essential tools and services that empower our software teams and improve build, test, deployment, and productisation of ML software components.

You will work with HPC AI platforms and gain experience in distributed systems, while collaborating on CI/CD pipelines, Kubernetes, Terraform and observability tooling to support fast, reliable ML workloads.

Qualifications

• Proficient Python development and Linux expertise.
• Experience in cloud services (AWS) and CI/CD pipelines.
• Experience deploying and maintaining ML applications and orchestration tools.
• Familiarity with Kubernetes, Docker, and ML accelerator hardware.

Responsibilities

• Develop, own, and maintain tools and services for AI research and engineering teams.
• Deploy and maintain services with Kubernetes and Docker.
• Manage our Cloud Infrastructure using Terraform and OpenTofu.

Skills

Python

AWS

Linux

CI/CD

ML applications

ML orchestration

NVIDIA Ray

Terraform

OpenTofu

GitHub Actions

Prometheus

Grafana

Kubernetes

Docker

Go

Java

C++

Go/Java/C++

Tools

Terraform

OpenTofu

AWS cloud services

Job description

Graphcore in the United Kingdom is seeking a Software Infrastructure Engineer to scale and manage our infrastructure. You will develop essential tools and services that empower our software teams and improve build, test, deployment, and productisation of ML software components.

You will work with HPC AI platforms and gain experience in distributed systems, while collaborating on CI/CD pipelines, Kubernetes, Terraform and observability tooling to support fast, reliable ML workloads.