Senior Software Engineer (ML QA)
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About the role
Help prove the ML software stack that future AI systems will depend on. Graphcore is expanding the software systems behind AI compute at datacenter scale. This role focuses on validating a complex machine learning stack before it reaches customers and hardware.You will build the test infrastructure, automation and tooling that engineers trust every day. Your work will help raise reliability, performance and maintainability across frameworks, simulators, emulators and future hardware. You will shape test architecture across large codebases, CI pipelines and representative ML workloads. You will use strong software engineering judgement to turn complex technical goals into scalable validation systems. This is a role for someone who enjoys depth, ownership and useful engineering. You will make quality easier, faster and more visible for teams building at the edge of AI compute. The team and culture The ML QA team sits where Graphcore's software components come together. Engineers work across unit tests, integration tests, full model runs, subgraph validation and benchmarking. Work is organised through focused squads with clear ownership. People are expected to step up, speak openly and improve how the team builds, tests and learns. Decisions are grounded in evidence from code, data and system behaviour. The team works closely with software teams to identify gaps, improve tooling and move priorities forward quickly.
Requirements
- Strong software design skills, with experience building maintainable systems across large codebases.
- Production Python experience, including testable, reliable code used by other engineers.
- Experience with CI/CD, automated testing and Linux based development workflows.
- Familiarity with C or C++, with confidence reading and debugging low level code.
- Understanding of ML frameworks, workloads or model execution beyond simple API usage.
- Ability to mentor engineers, improve practices and take ownership of complex technical problems.
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