SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Graphcore is seeking a Staff Software Engineer to build and architect the software that validates Graphcore's machine learning stack, from frameworks to AI accelerator hardware.
In this role, you will design production-quality test infrastructure that engineers across the company can extend, maintain and rely on as the ML software grows. You'll architect scalable test frameworks and build CI/CD pipelines that run across simulators, emulators and physical hardware. Your work will help teams deliver reliable products with clear evidence of numerical accuracy and performance across the entire stack.
You'll create representative ML workloads, analyse their execution, and turn results into practical improvements to testing and tooling. This is not a role limited to adding tests to existing systems—you'll have scope to shape software architecture and developer experience, deepening your understanding of the AI compute stack while solving engineering problems that connect software design with hardware behaviour.
The ML QA team builds automation, works with industry-standard frameworks and models, and contributes to upstream open-source projects. You'll work across software teams, using code and design reviews to strengthen quality, security and maintainability. You'll own improvements, act quickly on testing gaps, and mentor junior engineers to raise the team's technical standards. Your workload results will challenge assumptions and guide technical decisions about how Graphcore tests its ML stack.
Graphcore is one of the world's leading innovators in AI compute, developing hardware, software and systems infrastructure to unlock the next generation of AI breakthroughs. As part of the SoftBank Group, Graphcore is positioned at the forefront of AI infrastructure innovation.
REQUIREMENTS:
- Strong Python skills, demonstrated through designing, developing and maintaining production-quality software
- Software design and architecture skills for large, complex codebases, with a focus on testability and long-term maintainability
- 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
- The ability to mentor junior engineers and influence engineering practices through constructive feedback
- A self-directed approach to solving complex problems, identifying gaps and driving improvements
The company welcomes transferable skills and diverse experiences, including engineers returning to the profession after a career break.
