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Staff Software Engineer (ML Quality Assurance)

Graphcore

Skills

Required

  • CI/CD pipelines
  • automated testing systems
  • Linux environments
  • C++
  • Python
  • Software design
  • codebases
  • testability

Preferred

  • CI/CD

Join Graphcore as a Staff Software Engineer (ML Quality Assurance) and play a crucial role in validating the company's machine learning stack. You will design production-quality test infrastructure, architect scalable test frameworks, and create representative ML workloads. This position offers the opportunity to shape software architecture, deepen your understanding of the AI compute stack, and mentor junior engineers. Enjoy a flexible work-life balance, private medical insurance, a pension plan, and a focus on learning and development.

Responsibilities

  • Concevoir et mettre en œuvre une infrastructure de test de qualité de production que les ingénieurs peuvent étendre, maintenir et utiliser.
  • Architecturer des frameworks de test évolutifs et construire des pipelines CI/CD qui fonctionnent sur des simulateurs, des émulateurs et du matériel physique.
  • Créer des charges de travail ML représentatives, analyser leur exécution et transformer les résultats en améliorations pratiques pour les tests et les outils.
  • While we have outlined a set of requirements, we value transferable skills and diverse experiences. We also welcome engineers returning to the profession after a career break, including through returnship routes
  • A self-directed approach to solving complex problems, identifying gaps and driving improvements

Requirements

  • Experience building CI/CD pipelines and automated testing systems in Linux environments
  • Familiarity with C or C++, including the ability to read, debug and reason about low-level code
  • Strong Python skills, demonstrated through designing, developing and maintaining production-quality software
  • The ability to mentor junior engineers and influence engineering practices through constructive feedback
  • Software design and architecture skills for large, complex codebases, with a focus on testability and long-term maintainability