Graphcore
AI compute
MLQATechnicalProductOwner
Neural analysis suggests this role is
optimal for Mid candidates.
“ML QA Technical Product Owner at Graphcore. Skills: ML QA, Technical Product Owner, backlog management, roadmaps, validation strategies, technical collaboration. Own and Shape the Component Backlog. Create and maintain team roadmaps for the Program Increment (PI) and long term plan”
Industry & Context.
solve the toughest problems
Applicants for this position must hold the right to work in the UK, unable to provide visa sponsorship or support for visa applications
What They're Looking For.
Must Have
Experience working as a Product Owner (or similar role) in an agile environment, Ability to communicate clearly with both technical and non-technical stakeholders, 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, Right to work in the UK
Nice to Have
Certified Scrum Product Owner (CSPO) or Professional Scrum Product Owner (PSPO), Experience of working in SAFe / Scrum@scale, Experience with Atlassian Tool Suite, Experience working with machine learning software, ML infrastructure, or performance benchmarking environments
What You'll Do.
Own and Shape the Component Backlog
Create and maintain team roadmaps for the Program Increment (PI) and long term plan
Translate feature-level intent into actionable Software QA work
feedback team intent and challenges to help shape the features
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
and delivery expectations
Support Delivery Across Sprints and Planning Increments
Actively support sprint planning
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
Ensure the backlog is sufficiently maintained to prepare for PI planning
identifying dependencies and risks early
aligning with other teams on the scope taken into planning
Ensure your team’s work aligns with agreed PI objectives
Coordinate Validation Across Teams
Coordinate feature validation planning with teams working across ML frameworks
distributed execution
and integration activities are planned early as part of feature development
Facilitate communication between teams to identify risks
and changing priorities
Enable Effective Technical Collaboration
Develop sufficient technical understanding of the ML software stack and validation workflows
Help prioritise validation coverage for new features
performance improvements
Support constructive technical discussions while balancing delivery priorities and quality expectations
Help remove organisational blockers and improve coordination across teams and stakeholders
How You'll Work.
Team & Collaboration
collaborates closely with software engineering teams throughout the development lifecycle; 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; Facilitate communication between teams to identify risks, blockers, and changing priorities; engage effectively with engineers and stakeholders; improve coordination across teams and stakeholders
Communication Scope
Ability to communicate clearly with both technical and non-technical stakeholders; Ability to simplify and present complex information; Facilitate communication between teams
Process & Methodology
backlog management, refinement skills, product vision, roadmaps, PI planning, sprint planning, delivery expectations, coordination
Full Job Description
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 stakehol
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