Salary Range: PLN 350,700 - 474,400 + Benefits + Equity
Subject to alignment to the responsibilities and duties of the role.
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 builds and runs measurements on large-scale Linux clusters—from a single rack up to datacentre-scale systems. We use these measurements to determine system performance, reliability, and whether a system can be trusted in production. You will work across: Designing and running measurements on distributed systems Analysing performance and reliability results Improving systems that execute measurements at scale Typical work includes: Running measurements on large-scale Linux clusters (rack-level and beyond) Using and extending tools such as pytest for measurement execution Measuring compute, network, and ML workload performance Analysing variability and repeatability of results Engineers in this team are not limited to a single area. You may work on infrastructure, workloads, or analysis depending on the problem. You are free to specialise, but the team is responsible for ensuring complete coverage. This role is not purely infrastructure or data analysis. It combines systems engineering, measurement, and interpretation. We are looking for engineers who: Are comfortable working with distributed systems at scale Can reason about performance and reliability Prefer clear, evidence-based conclusions over assumptions 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.