Build and maintain infrastructure, tools and services to support AI research and engineering. Deploy and operate services with Kubernetes and Docker, manage cloud infrastructure (Terraform/AWS), support CI/CD, and enable ML application deployment, orchestration, and accelerator hardware management.

Conduct hardware-aware AI research: generate ideas, design and run ML experiments, implement performant scalable systems, publish and present results, and collaborate with researchers, silicon and software engineers to guide next-generation AI hardware.

Develop, implement and optimise large-scale ML models for Graphcore hardware; benchmark and scale training/inference across thousands of accelerators; test internal releases, fix and review code; design and run experiments; collaborate with Research, Software and Product teams; engage with the AI community.