At a Glance
- Tasks: Transform large-scale system measurements into actionable insights for AI compute.
- Company: Join Graphcore, a leader in AI technology backed by SoftBank.
- Benefits: Enjoy flexible working, generous leave, private health insurance, and more.
- Other info: Inclusive culture with opportunities for growth and collaboration.
- Why this job: Make a real impact on the future of AI with cutting-edge technology.
- Qualifications: Strong software engineering skills, especially in Python and Linux environments.
The predicted salary is between 60000 - 80000 £ per year.
About Graphcore
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, 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
We turn large‑scale system measurements into decisions. Our team runs workloads across clusters of machines and collects detailed performance data. The challenge isn’t running the measurements—it’s deciding what they mean, and whether a system is good enough to enter production.
You will work with results from real systems and help answer questions like:
- Is this system behaving as expected?
- Is performance stable enough to trust?
- Does this meet the criteria to enter production?
This work includes systems engineering and analysis. It involves understanding variability, repeatability, and the differences between signal and noise. You won’t be confined to a single role. You may shape measurements, influence how they are run, or improve how results are interpreted. You are free to specialise, but the team is responsible for leaving no gaps. This is not a dashboarding or reporting role in the traditional sense. The goal is to produce outputs that support real engineering decisions.
We’re looking for engineers who:
- Think carefully about uncertainty and evidence
- Prefer clarity over presentation
- Are comfortable challenging conclusions when data is weak
Selection criteria:
Our engineers typically bring significant practical experience and sound engineering judgment. Depth in one area is valued, but the ability to work across boundaries is equally important.
- Strong software engineering experience, typically gained across multiple projects or systems over several years
- Experience working in Linux‑based environments, ideally with distributed or high‑performance systems
- Proficiency in Python
- Experience with automation and CI/CD systems (e.g. GitLab CI, Jenkins, GitHub Actions)
- Ability to design, implement, and run experiments or tests that produce meaningful results
- Ability to interpret results and communicate findings clearly, with an emphasis on accuracy and usefulness to decision‑making
- Comfortable working in areas where requirements are not fully defined and judgment is required
- Experience working with large‑scale or distributed systems (e.g. clusters, cloud platforms, HPC environments)
- Experience with performance, reliability, or systems‑level testing/measurement
- Familiarity with pytest or similar frameworks for structured test/measurement execution
- Experience analysing system behaviour under load (compute, network, or ML workloads)
- Experience working with containerisation, orchestration, or provisioning systems (e.g. Docker, Kubernetes, OpenStack)
- Proficiency in other applications programming languages (e.g. C++)
- Exposure to data analysis, statistics, or interpreting variability in results
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.
Sponsorship
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 Systems Engineer – Performance & Reliability (Analysis) London, UK employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Systems Engineer – Performance & Reliability (Analysis) London, UK
✨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 might just get your foot in the door.
✨Tip Number 2
Prepare for the interview by diving deep into performance and reliability topics. Brush up on your Python skills and be ready to discuss how you've tackled similar challenges in the past.
✨Tip Number 3
Showcase your problem-solving skills during interviews. Be ready to explain how you approach uncertainty and make decisions based on data—Graphcore loves engineers who think critically!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team.
We think you need these skills to ace Senior Systems Engineer – Performance & Reliability (Analysis) London, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your software engineering experience, especially in Linux-based environments and Python, as these are key for us.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about performance and reliability in systems engineering. Share specific examples of how you've tackled similar challenges in the past.
Showcase Your Problem-Solving Skills: In your application, emphasise your ability to interpret results and make decisions based on data. We love engineers who can think critically about uncertainty and evidence!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team.
How to prepare for a job interview at graphcore
✨Know Your Systems Inside Out
Make sure you have a solid understanding of systems engineering principles, especially in performance and reliability. Brush up on your experience with Linux-based environments and distributed systems, as these will be key topics during the interview.
✨Prepare for Data Interpretation Questions
Expect questions that challenge your ability to interpret performance data. Be ready to discuss how you would approach analysing system behaviour under load and what metrics you would consider important for making engineering decisions.
✨Showcase Your Software Skills
Highlight your proficiency in Python and any other programming languages you know, like C++. Be prepared to discuss your experience with automation and CI/CD systems, as well as how you've used these tools in past projects.
✨Emphasise Problem-Solving Abilities
Graphcore values engineers who can think critically about uncertainty and evidence. Prepare examples from your past work where you had to challenge conclusions based on weak data or navigate ambiguous requirements.