Senior Engineer (ML Engineer)

About the company Graphcore builds AI compute hardware and software, developing the complete AI compute stack from silicon and software to datacenter-scale infrastructure. Part of the SoftBank Group, the company is expanding globally to meet growing demand in the AI ecosystem. About the role This is a hands-on ML engineering role focused on testing, validating, and benchmarking a complex ML software stack across performance, reliability, and correctness dimensions. You'll work within the ML QA team, bringing up state-of-the-art models on internal infrastructure and collaborating with software and hardware teams on AI accelerator technology. Responsibilities - Benchmark ML models and frameworks, analysing results to identify regressions, performance bottlenecks, and correctness issues - Validate functionality and performance of industry-standard ML frameworks across different execution environments - Build and maintain automated testing and benchmarking pipelines targeting simulators, emulators, and physical hardware - Collaborate with software teams to ensure adequate test coverage for new and existing features - Develop Python tooling and scripts to support testing, benchmarking, and functional reporting - Own aspects of testing and infrastructure, driving roadmap and innovation independently Requirements - Experience in Machine Learning or ML-adjacent engineering roles - Strong foundation in core AI/ML concepts (neural networks, training vs inference, numerical precision, performance trade-offs) - Hands-on experience with PyTorch, TensorFlow, JAX, or similar ML frameworks - Strong Python proficiency for ML workflows, experimentation, and automation - Experience designing, running, and analysing ML benchmarks or experiments - Experience working in Linux environments - Bachelor's, Master's, or PhD (or equivalent) in Computer Science, Maths, ML, Data Science, or related field - Must hold the right to work in the UK (no visa sponsorship available) Nice to have - MLOps pipelines, model deployment, or production ML systems experience - Familiarity with performance profiling tools or numerical accuracy validation - Exposure to distributed training or inference systems - Experience with hardware-accelerated ML, compilers, or system-level performance - CI/CD systems experience for ML workflows - Open-source ML framework contributions Benefits & perks - Flexible working and generous annual leave policy - Private medical insurance, health cash plan, and dental plan - Pension matched up to 5%, life assurance, and income protection - Generous parental leave policy and employee assistance programme - Free healthy food, snacks, and barista bar at Bristol office Compensation Competitive salary (amount not specified). No equity or bonus details mentioned.