qa engineer (auto) for AI compute

Graphcore develops hardware, software and systems infrastructure for Artificial Intelligence compute, enabling the next generation of AI breakthroughs and wider adoption of AI solutions across industries.

• Validate the ML stack that turns accelerator hardware into trusted AI performance;
• Test, benchmark and validate complex systems before they reach customers;
• Identify regressions, correctness issues and performance limits across frameworks, models and execution environments;
• Run open source models;
• Build automated benchmarking pipelines;
• Create targeted tests for low-level ML behaviour, including numerical precision, quantisation, attention mechanisms, distributed execution and model subgraphs;
• Improve the reliability of AI models running on advanced infrastructure;
• Contribute to validation across unit tests, full model benchmarks, distributed workloads, simulators, emulators and hardware targets;
• Take ownership of testing quality and improve testing practices;
• Work closely with software, infrastructure and hardware teams;
• Shape roadmaps and raise the quality bar.

• Strong experience in Machine Learning or ML-adjacent software engineering roles;
• Solid understanding of neural networks, training, inference, numerical precision and performance trade-offs;
• Strong Python skills for automation, experimentation, benchmarking and reporting;
• Experience designing, running and analysing ML benchmarks or model experiments;
• Confident debugging skills in Linux;
• Nice to have: hands-on experience with PyTorch, TensorFlow, JAX, Triton or similar ML frameworks and tools.

• Unlimited annual leave;
• Up to 5% matched pension;
• Phantom equity – share in Graphcore’s success;
• True flexibility in how and where you work;
• Office spaces designed for collaboration;
• Free food and an on-site barista;
• Health cash plan;
• Income protection;
• Life assurance;
• Other selectable benefits, including private medical insurance and dental plan.