At a Glance
- Tasks: Design and maintain robust test infrastructure for cutting-edge ML software.
- Company: Join Graphcore, a leader in AI compute backed by SoftBank.
- Benefits: Enjoy flexible working, generous leave, private medical insurance, and more.
- Other info: Collaborate with top minds in a dynamic, inclusive environment.
- Why this job: Make a real impact in the fast-growing AI ecosystem with innovative technology.
- Qualifications: Strong software engineering skills, especially in Python and CI/CD systems.
The predicted salary is between 60000 - 80000 £ per year.
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 datacentre 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 Summary
Applicants 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 Team
The 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.
Candidate Profile
- 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.
- 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.
Staff ML QA Engineer - Build Robust ML Software & Tests employer: graphcore
Graphcore is an exceptional employer, offering a dynamic work environment in the heart of Bristol where innovation thrives. With a strong focus on employee growth, we provide extensive mentoring opportunities and a culture that values collaboration and quality. Our comprehensive benefits package, including flexible working arrangements, generous leave policies, and health support, ensures that our team members are well taken care of while contributing to groundbreaking advancements in AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML QA Engineer - Build Robust ML Software & Tests
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Graphcore. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a GitHub or portfolio, make sure it's up to date. Share projects that highlight your experience with ML frameworks and CI/CD systems – it’s a great way to stand out!
✨Tip Number 3
Prepare for the interview by brushing up on your problem-solving skills. Expect technical questions that dive deep into software design and architecture. Practice coding challenges to keep your skills sharp!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Staff ML QA Engineer - Build Robust ML Software & Tests
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Staff ML QA Engineer role. Highlight your experience with software design, testing, and automation, as these are key aspects of what we're looking for at Graphcore.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that showcase your proficiency in Python, CI/CD systems, and any relevant machine learning frameworks. We want to see how you’ve applied your knowledge in real-world scenarios.
Be Clear and Concise:When writing your application, keep it clear and to the point. Avoid jargon unless it's necessary, and make sure your passion for AI and software quality shines through. We appreciate straightforward communication!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're genuinely interested in joining our team at Graphcore!
How to prepare for a job interview at graphcore
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning frameworks like PyTorch and TensorFlow. Be ready to discuss your experience with CI/CD systems and how you've implemented automated testing in past projects. This will show that you're not just familiar with the tools, but that you can effectively use them in a production environment.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex problems you've tackled in software engineering. Think about challenges related to software architecture or maintaining code quality. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to follow your thought process.
✨Emphasise Collaboration
Graphcore values teamwork, so be ready to discuss how you've worked with other engineers in the past. Highlight any mentoring experiences you've had, especially if you've helped junior engineers improve their skills. This shows that you’re not only a strong individual contributor but also someone who can uplift the team.
✨Ask Insightful Questions
Prepare some thoughtful questions about the team dynamics, the technologies they use, or the challenges they face. This demonstrates your genuine interest in the role and helps you assess if the company culture aligns with your values. Plus, it gives you a chance to engage in a meaningful conversation with your interviewers.
