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Software Engineer, Data Enrichment

Wayve · London, United Kingdom

Confidence
High confidence
Posted
2 Oct 2026
First seen
24 Oct 2026
Last checked

Evidence

High confidence

The posting says Wayve sponsors visas, and Wayve is on the UK Home Office register.

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UK Home Office Register of Licensed Sponsors

Listed as Wayve Technologies Ltd. London · Skilled Worker route · A rating. Snapshot 26 Oct 2026.

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Job posting

Relocation support and visa sponsorship where applicable

On jobs.ashbyhq.com/wayve, read 26 Oct 2026.

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Seen on the job board

First seen 24 Oct 2026. We check every day and remove closed roles.

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jobs.ashbyhq.com/wayve

Wayve’s job board, hosted by Ashby.

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 Data Enrichment Platform Team Our Enrichment Orchestration team builds the platform that enables Wayve’s teams to deploy, run, evaluate and continually improve machine-learning models. Processing petabytes of driving data across large GPU fleets, the team creates dependable, self-service capabilities that help model engineers understand model performance, improve quality and reduce operational effort and cost.

Your day-to-day - Design, build and operate backend services, APIs and data-processing workflows for the Data Enrichment Platform. - Develop model-execution workflows, versioned outputs, annotation capabilities and dataset-catalogue features. - Improve the scalability and reliability of systems for large-scale inference, automated evaluation and model monitoring. - Investigate and resolve reliability, performance and cost issues across petabyte-scale data and GPU-backed workloads. - Contribute to designs covering data locality, scheduling, capacity, backpressure, failure recovery and observability. - Collaborate with model engineering, AI Platform, infrastructure, compute, storage and data teams to deliver reusable capabilities.

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