Infrastructure and MLOps Engineer

Graphcore is hiring an Infrastructure and MLOps Engineer in Cambridge, United Kingdom. Level rates it ; you can apply on Graphcore.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Python, Kubernetes and Docker.
Level classifies it as a mid-level role.
Level lists 196 other open roles at Graphcore.

AI in this role

Build and maintain infrastructure, CI/CD pipelines, and tools supporting AI research and machine learning software platforms.

PythonKubernetesDockerTerraformAWSLinuxGitHub ActionsPrometheusGrafana

ml-opsai-researchmlopsinfrastructureci-cddistributed-systemshigh-performance-computing

About Graphcore

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems

The Team

The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible.

Responsibilities and Duties

Develop, own, and maintain tools and services to support AI research and engineering teams

Deploy and maintain services with Kubernetes and Docker

Manage our Cloud Infrastructure using tools such as Terraform

Candidate Profile

Essential:

Knowledge of Python

Familiarity with cloud services (e.g. AWS)

Experience managing or developing in Linux environments

Understanding of CI/CD principles

Experience using Kubernetes (k8s)
Experience of one of the following:
maintaining machine learning applications.
deploying ML orchestration tools (e.g. NV Ray, KFP, SkyPilot).
managing ML accelerator hardware (e.g. DCGM).

Desirable

Experience with Infrastructure as Code (IaC) tools (e.g. Terraform/OpenTofu)

Experience with GitHub Actions

Experience with modern observability tooling (e.g. Prometheus)

Experience with Grafana

Knowledge of Go/Java/C++ (or similar language)
Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

How we rate this

Infrastructure and MLOps Engineer at Graphcore rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Infrastructure and MLOps Engineer is an open job at Graphcore.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Cambridge, UK.
The job was posted on July 16, 2026.
Seniority: mid.
Applications are handled by Graphcore. Apply on Graphcore

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsAI ResearchMLOpsInfrastructureCI/CDDistributed SystemsHigh Performance ComputingPython

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a research question you investigated. What did you find?
Tell me about a project where mlops was part of your work. What did you do?
Tell me about a project where infrastructure was part of your work. What did you do?
Tell me about a project where ci/cd was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ML Ops, AI Research, MLOps, Infrastructure, and CI/CD. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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