Requirements
* Experience working as a Product Owner (or similar role) in an agile environment
* Ability to communicate clearly with both technical and non-technical stakeholders
* Strong backlog management and refinement skills
* Proven experience in developing product vision and roadmaps
* Ability to understand and discuss technical concepts related to software development, testing, or infrastructure
* Strategic mindset with empathy and ability to bring calm, clarity and support
* Excellent facilitation skills, ability to guide discussions / events to conclusion
* Ability to simplify and present complex information
* Confidence working with technical teams and complex systems
* Experience coordinating work across multiple teams or components
* (Desirable) Certified Scrum Product Owner (CSPO) or Professional Scrum Product Owner (PSPO)
* (Desirable) Experience of working in SAFe / Scrum@scale
* (Desirable) Experience with Atlassian Tool Suite
* (Desirable) Experience working with machine learning software, ML infrastructure, or performance benchmarking environments
What the job involves
* The ML QA teamis responsible forvalidatingthe machine learning software stack running onGraphcorehardware
* 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 tovalidatecorrectness, 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 roadmapobjectives
* 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
* Ensure all work is clearly linked to higher-level product outcomes
* Work with engineers and technical leads to refine acceptance criteria, validation scope, and delivery expectations
* Support Delivery Across Sprints and Planning Increments
* Actively support sprint planning, reviews, demos, providing visual outputs that demonstrate progress against the plan, learnings and changes
* Involve the team in the right discussions to ensure desired outcomes are realistic, and the team’s ability to deliver them are clearly communicated
* Ensure the backlog is sufficiently maintained to prepare for PI planning, identifying dependencies and risks early and aligning with other teams on the scope taken into planning
* Ensure your team’s work aligns with agreed PI objectives
* Coordinate Validation Across Teams
* Work closely with Technical Product Owners, Product Managers, engineering teams, and technical leads to manage dependencies and alignment
* Coordinate feature validation planning with teams working across ML frameworks, runtime systems, performance tooling, distributed execution, and infrastructure
* Help ensure testing, benchmarking, and integration activities are planned early as part of feature development
* Facilitate communication between teams toidentifyrisks, blockers, and changing priorities
* Enable Effective Technical Collaboration
* Develop sufficient technical understanding of the ML software stack and validation workflows to engage effectively with engineers and stakeholders
* Help prioritise validation coverage for new features, performance improvements, and software changes
* Support constructive technical discussions while balancing delivery priorities and quality expectations
* Help remove organisational blockers and improve coordination across teams and stakeholders
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