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 SummaryApplicants for this role should have strong experience designing, developing, and maintaining high-quality software systems. The role focuses on testing and validating a complex machine learning software stack, with particular emphasis on software architecture, automation, and engineering best practices.
The ideal candidate is an experienced software engineer who values code quality, testability, and long-term maintainability, and enjoys building systems that other engineers rely on. This person will be comfortable working across large codebases, contributing to CI/CD infrastructure, and shaping technical direction through thoughtful design and mentoring in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware
The TeamThe ML QA team is composed of highly skilled software engineers with a strong focus on automation, software quality, and data-driven validation. The team works closely with industry-standard machine learning frameworks and models, contributing to upstream open-source projects and collaborating across the wider software organization.
Operating in a fast-paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high-quality products to customers.
Responsibilities and Duties- Design, implement, and maintain robust test infrastructure and automation for a complex ML software stack.
- Architect and evolve test frameworks and tooling with a focus on scalability, maintainability, and developer experience.
- Build and maintain CI/CD pipelines targeting simulators, emulators (e.g. QEMU), and physical hardware.
- Create representative ML workloads and gain insights from their execution. (Numerical accuracy, performance analysis and benchmarking).
- Work closely with all Software development teams, supporting a culture of quality, security and maintainability.
- Review code and designs, setting a high bar for software engineering best practices.
- Mentor and support junior engineers, helping raise the overall technical capability of the team.
- Evaluate existing test strategies and infrastructure, identifying gaps and driving improvements aligned with team and organizational goals.
Essential:
- Experience in production-quality software engineering roles.
- Strong software design and architecture skills, with experience working on large or complex systems.
- Strong proficiency in Python, including experience building and maintaining production codebases.
- Solid experience with CI/CD systems and automated testing (preferably GitHub-based workflows).
- Experience working in Linux environments.
- Familiarity with C or C++, with the ability to read, debug, and reason about low-level code when needed.
- Proven ability to mentor junior engineers and influence engineering practices within a team.
- Strong problem-solving skills and a proactive, self-directed approach to work.
- Bachelor/Master's/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field.
Desirable
- Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow
- Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines
- Experience working with hardware simulators or emulators (e.g. QEMU).
- Experience developing for or working with FPGA-based systems.
- Experience with people management or mentoring
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.
Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications
Top Skills
What We Do
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.
Why Work With Us
Our team is at the forefront of the machine intelligence revolution, enabling innovators from all industries to build AI-native products to expand human potential. What we do at Graphcore really makes a difference.
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Graphcore Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
At Graphcore, we value wellbeing and flexibility to support a healthy work/life balance. Our hybrid approach encourages office-based colleagues to work onsite three days a week, with trusted flexibility built on trust and transparency for everyone.





