Senior Software Engineer (ML QA)

Senior Software Engineer (ML QA)

Full-Time 60000 - 80000 € / year (est.) Home office (partial)
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 environment with excellent career growth and mentoring opportunities.
  • Why this job: Make an impact on the future of AI while working with cutting-edge technology.
  • Qualifications: Experience in software engineering, strong Python skills, 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.

Senior Software Engineer (ML QA) 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 makes Graphcore a fantastic place for talented individuals to make a meaningful impact in the rapidly evolving field of AI.

graphcore

Contact Detail:

graphcore Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Software Engineer (ML QA)

Tip Number 1

Network like a pro! Reach out to current employees at Graphcore on LinkedIn or other platforms. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.

Tip Number 2

Prepare for the technical interview by brushing up on your coding skills and ML concepts. Practice common algorithms and system design questions, and don’t forget to showcase your experience with CI/CD and Python during discussions.

Tip Number 3

Showcase your passion for AI and software quality! During interviews, share examples of how you've improved code quality or mentored others. This will highlight your fit for the team’s culture and values.

Tip Number 4

Don’t just apply through job boards; head over to our website and submit your application there. It shows you're genuinely interested in being part of the Graphcore family, and we love that!

We think you need these skills to ace Senior Software Engineer (ML QA)

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

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with software design, architecture, and testing. We want to see how your skills align with the role of Senior Software Engineer (ML QA) at Graphcore.

Showcase Your Projects:Include examples of your past work that demonstrate your proficiency in Python and CI/CD systems. We love seeing real-world applications of your skills, especially if they relate to machine learning or complex software systems.

Highlight Your Mentoring Experience:If you've mentored junior engineers or influenced engineering practices, make sure to mention it! We value a collaborative spirit and want to know how you can contribute to our team's growth.

Apply Through Our Website:For the best chance of success, apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you’re considered for the role!

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 work with.

Showcase Your Problem-Solving Skills

Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Graphcore values strong problem-solving skills, so think of examples where you’ve had to innovate or adapt quickly. This will demonstrate your proactive approach and ability to thrive in a fast-paced environment.

Emphasise Code Quality and Best Practices

Be ready to talk about your experience with code reviews and setting high standards for software engineering practices. Mention any mentoring you've done, as they’re looking for someone who can help raise the technical capability of the team. This shows you value quality and are willing to contribute to a culture of excellence.

Ask Insightful Questions

Prepare thoughtful questions about the team’s current projects, challenges they face, or their approach to automation and testing. This not only shows your interest in the role but also helps you gauge if the company culture aligns with your values. Plus, it gives you a chance to engage with your interviewers on a deeper level.