
Senior Machine Learning Engineer, AV Core
Wayve · London, United Kingdom · Remote possible
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.
Still open
Seen on the job board
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 AV Core Engineering Team Wayve’s AV Core organisation builds the foundational capabilities required for assisted and fully autonomous driving. Within AV Core, the Core Model Safety team focuses on collision avoidance, model understanding, and robustness under failure. You’ll join a focused, high-impact senior team working with large-scale training and fleet data, alongside partners in research, simulation, evaluation, and applied engineering.
Your day-to-day You’ll lead large-scale data enrichment and curation initiatives, collaborating across pre- and mid-training, reward modelling, self-supervised labelling, and the Data Enrichment Platform. You’ll develop workflows for mining hard and rare events, investigate how models perform in the real world, and improve the efficiency and reliability of our machine learning operations stack. What you’ll be working on - Lead on large-scale data enrichment within the Core Model Safety team, including collaborations with Pre/Midtraining, reward modelling, self-supervised labelling, and the Data Enrichment Platform.
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