Jobs at Graphcore

Lead discovery and design for large transformation programmes: map current processes, define requirements, design future-state workflows, analyse systems and data, support testing and implementation, and drive stakeholder alignment to ensure successful adoption and measurable business outcomes.

Validate and benchmark ML models on Graphcore's software/hardware stack. Create automated benchmarking pipelines, run open-source models, design targeted tests for numerical precision, quantisation, attention, distributed execution, and debug performance and correctness issues across frameworks and environments.

Design and build test infrastructure, automation, and tooling to validate ML software stacks and hardware; shape test architecture across CI pipelines, frameworks, simulators, emulators, and large ML workloads; mentor engineers and own complex validation projects.

Validate and benchmark ML models and stacks on Graphcore hardware. Build automated benchmarking pipelines, run open-source models, create targeted tests for numerical precision, quantisation, distributed execution and subgraphs, and debug performance and correctness across frameworks and execution environments.

Build and operate Kubernetes-based infrastructure and tooling to support development, testing, deployment and scaling of Graphcores ML software. Manage cloud infrastructure, CI/CD practices, and collaborate with software teams to improve reliability and observability of HPC AI platforms.

Design, deploy, and maintain tools and services for build, CI/CD, packaging, and releases. Manage cloud and Kubernetes infrastructure, use IaC, reduce toil, and support junior engineers for reliable ML software delivery.

Develop and maintain internal build, test, and integration tooling for the ML software stack. Build release processes, assist dependency management, guide developers on build best practices, collaborate with QA and engineers to resolve integration issues, and contribute fixes to the ML software stack.

Develop, manage, and sustain tools and services for software build, test, deployment, and release. Build and maintain API integrations and automation workflows, support Linux-based environments, and improve reliability while reducing operational toil. Mentor junior and graduate engineers and collaborate across engineering and security teams.

The Senior Systems Engineer focuses on analyzing performance data from systems, ensuring stability for production, and using engineering judgment for decision-making in a high-performance computing context.

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 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.

Develop and deploy cloud services, optimize AI systems, and work on infrastructure automation while collaborating with various teams.

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 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.