ML QA Technical Product Owner
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About the Role
About Graphcore
At Graphcore, we’re building the future of AI compute.
We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.
As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.
To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.
We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.
The Team
The ML QA team is responsible for validating the machine learning software stack running on Graphcore hardware. The team works across integration testing, feature validation, performance benchmarking, and end-to-end workload testing, covering multiple layers of the software stack including ML frameworks, runtime behaviour, distributed execution, and system-level functionality.
The team collaborates closely with software engineering teams throughout the development lifecycle, helping define validation strategies early and implementing the test coverage required to validate correctness, functionality, scalability, and performance. The ML QA team also owns performance-focused validation, including benchmark execution, regression analysis, and reporting across real-world ML workloads and extracted model subgraphs.
As Technical Product Owner for ML QA, you will help coordinate and prioritise this work, ensuring the team has clear direction, well-defined deliverables, and alignment with wider software roadmap objectives.
Responsibilities and Duties
Own and Shape the Component Backlog
- Create and maintain team roadmaps for the Program Increment (PI) and long term plan to help visualise the current backlog and communicate status and progress to all stakeholders.
- Translate feature-level intent into actionable Software QA work and feedback team intent and challenges to help shape the features with the Technical Product Manager.
- Maintain a clear, prioritised backlog of Epics and Stories for the Software QA team.&a
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