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Conduct research in visual generative modelling, multimodal learning and world models; design and run experiments, publish findings, and collaborate with engineering and silicon teams to align models with hardware-aware ML and AI compute.

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.

The engineer will evaluate large-scale Linux systems, design workloads, build execution systems, interpret results, and ensure reliability for production readiness.

The Project Manager at Graphcore oversees cross-functional transformation projects, ensuring effective delivery, stakeholder collaboration, and process improvements across various teams.

As a Staff Software Engineer (ML QA), you'll design and maintain testing infrastructure for the ML software stack, focusing on automation, software quality, and mentoring junior engineers in a collaborative environment.

The role involves developing cloud platforms, deploying AI services, maintaining systems, and integrating third-party products in cloud environments.

Develop and deploy cloud services using Kubernetes, manage production workloads, and optimize AI systems. Collaborate with teams for continuous integration and infrastructure automation.

The Senior Cloud Platform Engineer will develop and operate high-performance infrastructure within private clouds, collaborate with Datacentre Operations, and support product delivery through effective automation and monitoring.

The Lead Analytics Engineer at Graphcore is responsible for developing and managing the analytics engineering layer, creating robust datasets and metrics, and collaborating with business stakeholders to enhance decision-making through reliable analytics.

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.