Senior Systems Engineer – Performance & Reliability

About this role

Requirements

• 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 judgement is required

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 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 Summary We decide whether entire racks of machines are good enough to enter production. Our team measures and evaluates large-scale Linux systems—from a single rack to data-centre scale. We don’t just run benchmarks; we determine whether a system behaves correctly, and whether it is reliable enough to be trusted. The work spans designing workloads, building execution systems, and interpreting results. A measurement is only useful if it leads to a decision. You won’t be confined to a narrow role. Some engineers here focus on infrastructure, others on workloads or analysis—but everyone contributes to understanding system behaviour at scale. You are free to specialise, but as a team we are responsible for leaving no gaps. You might find yourself: Expanding measurement coverage from small clusters to full racks Designing workloads that expose system behaviour Building systems to run experiments across large clusters Interpreting results and defining what “good enough” looks like This is not a pure infrastructure or data role. The work combines systems engineering, measurement, and judgement. We’re looking for engineers who are comfortable working where the right answer isn’t obvious, and where careful measurement matters more than output volume. Selection criteria: Our engineers typically bring significant practical experience and sound engineering judgement. Depth in one area is valued, but the ability to work across boundaries is equally important.