
Staff Validation Systems Engineer, AI Validation
Wayve · London, United Kingdom
Evidence
The posting says Wayve sponsors visas, and Wayve is on the UK Home Office register.
Sponsor register
UK Home Office Register of Licensed Sponsors
Listed as Wayve Technologies Ltd. London · Skilled Worker route · A rating. Snapshot 26 Oct 2026.
Job posting
Relocation support and visa sponsorship where applicable
On jobs.ashbyhq.com/wayve, read 26 Oct 2026.
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First seen 24 Oct 2026. We check every day and remove closed roles.
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Being on the register means Wayve can sponsor visas. It doesn’t confirm this role qualifies, so check with the recruiter.
About the role
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers.
ABOUT OUR ENGINEERING TEAMS Wayve’s engineering teams are building the AI, robotics, simulation, data, and systems foundations needed to deploy a generalisable AI Driver safely and at scale. ABOUT AI VALIDATION The AI Validation team develops the strategies, evidence, metrics, and test systems that build confidence in the Wayve AI Driver.
Both locations translate ambiguous product and safety questions into validation plans, scenarios, metrics, coverage, acceptance criteria, and evidence for release decisions—but the product scope and candidate profile differ by location. This role focuses primarily on ADAS and L2 autonomy functions. It works closely with automotive and OEM expectations, including product, customer, safety, and regulatory requirements. The role can be hired as a TC4 individual contributor or an M4 manager with responsibility for technical direction and team delivery. YOUR DAY-TO-DAY - Translate product, systems, and safety requirements into validation strategies, test scenarios, metrics, coverage requirements, and acceptance criteria. - Work hands-on with Python, evaluation pipelines, test implementation, simulation, and data analysis.
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