Staff ML QA Engineer — Build Scalable Testing for ML Stack

Graphcore; Greater London; Hybride; GBP 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Flexible working

Generous leave

5% pension matching

Phantom equity

On‑site barista and free food

Résumé du poste

Graphcore is seeking an ML QA Software Engineer to build production‑quality test infrastructure for its ML software stack, across frameworks, simulators, emulators and hardware. You will design scalable test frameworks, CI/CD pipelines and representative ML workloads to drive improvements in testing and tooling.

You will influence software architecture and developer experience, mentoring junior engineers while deepening your understanding of the AI compute stack and hardware behavior.

Qualifications

• Strong Python skills with production‑quality software experience.
• Software design for large codebases with a focus on testability and maintainability.
• Experience building CI/CD pipelines and automated testing systems in Linux environments.
• Familiarity with C or C++, including reading, debugging and reasoning about low‑level code.
• Ability to mentor junior engineers and influence engineering practices.
• Self‑directed approach to solving complex problems, identifying gaps and driving improvements.

Responsabilités

• Design production‑quality test infrastructure for Graphcore’s ML software stack.
• Architect scalable test frameworks and CI/CD pipelines across simulators, emulators and hardware.
• Create representative ML workloads, analyze execution results and translate findings into tooling improvements.
• Shape software architecture and developer experience beyond merely adding tests to existing systems.

Connaissances

Python

Software design

CI/CD pipelines

C/C++

Mentoring

Problem solving

Description du poste

Graphcore is seeking an ML QA Software Engineer to build production‑quality test infrastructure for its ML software stack, across frameworks, simulators, emulators and hardware. You will design scalable test frameworks, CI/CD pipelines and representative ML workloads to drive improvements in testing and tooling.

You will influence software architecture and developer experience, mentoring junior engineers while deepening your understanding of the AI compute stack and hardware behavior.