Staff ML QA Engineer - Test Automation & CI/CD

Staff ML QA Engineer - Test Automation & CI/CD

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
graphcore

At a Glance

  • Tasks: Design and maintain robust test infrastructure for complex ML software.
  • Company: Join Graphcore, a leader in AI compute backed by SoftBank.
  • Benefits: Flexible working, generous leave, private medical insurance, and more.
  • Other info: Inclusive culture with opportunities for mentorship and career growth.
  • Why this job: Make an impact in AI while working with cutting-edge technology.
  • Qualifications: Experience in software engineering, Python proficiency, and CI/CD knowledge.

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 - Test Automation & CI/CD 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 ample opportunities for mentorship and skill development, alongside competitive benefits such as flexible working arrangements, generous leave policies, and comprehensive health plans. Our commitment to inclusivity and a supportive culture ensures that every team member can make a meaningful impact in the rapidly evolving field of AI.

graphcore

Contact Details:

graphcore Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff ML QA Engineer - Test Automation & CI/CD

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 CI/CD, Python, and ML frameworks. Let your work speak for itself!

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 take that extra step to connect with us directly.

We think you need these skills to ace Staff ML QA Engineer - Test Automation & CI/CD

Software Design
Software Architecture
Python
CI/CD Systems
Automated Testing
Linux Environments
C or C++

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the role of Staff ML QA Engineer. Highlight your experience with software design, automation, and CI/CD systems. We want to see how your skills align with our needs!

Showcase Your Projects:Include specific projects that demonstrate your proficiency in Python and your experience with machine learning frameworks. We love seeing real examples of your work and how you've tackled complex problems.

Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and experiences quickly.

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!

How to prepare for a job interview at graphcore

Know Your Tech Stack

Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and CI/CD systems. Brush up on your knowledge of machine learning frameworks like PyTorch and TensorFlow, as well as any experience with hardware simulators or emulators. This will show that you’re not just a fit for the role but also genuinely interested in the tech they use.

Showcase Your Problem-Solving Skills

Prepare to discuss specific challenges you've faced in previous roles, particularly those related to software quality and automation. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how you approached complex problems and what impact your solutions had on the team or project.

Emphasise Collaboration and Mentoring

Since the role involves working closely with other teams and mentoring junior engineers, be ready to share examples of how you’ve collaborated in the past. Talk about your approach to fostering a culture of quality and how you’ve helped others grow technically. This will demonstrate your ability to contribute positively to their team dynamic.

Ask Insightful Questions

Prepare thoughtful questions about the team’s current projects, challenges they face, and their approach to software quality. This not only shows your interest in the role but also gives you a chance to assess if the company aligns with your values and career goals. It’s a two-way street, after all!