> Markdown version of [/jobs/ext/1326625-infrastructure-and-mlops-engineer](https://www.wearedevelopers.com/jobs/ext/1326625-infrastructure-and-mlops-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Infrastructure and MLOps Engineer - **Company:** Graphcore - **Location:** Bristol, UK - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, C++ (Programming Language), Cloud Computing, Continuous Integration, Distributed Systems, Github, Python (Programming Language), Linux System Administration, Machine Learning, Cloud Services, Prometheus, Software Engineering, Software Systems, Datadog, High Performance Computing, Grafana, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Build Process, Machine Learning Operations, Terraform, Docker - **Published:** July 18, 2026 - **Apply:** https://www.totaljobs.com/job/infrastructure-engineer/graphcore-job107710327 ## About the Role * 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) ## Description 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 ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices](https://www.wearedevelopers.com/videos/1582-llmops-driven-fine-tuning-evaluation-and-inference-with-nvidia-nim-nemo-microservices) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)