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Senior Machine Learning Engineer, ADAS

Wayve · 🇬🇧 London, United Kingdom

Sponsorship Verification Proof

✓ 🇬🇧 UK Home Office Licensed Sponsor

Employer is on the UK Home Office register of licensed sponsors.

UK Home Office Register of Licensed Sponsors (Skilled Worker route): listed as 'Wayve Technologies Ltd', London — Skilled Worker; Worker (A rating)

An official government register match confirms the employer holds an active sponsor licence in this country. It does not guarantee that every individual role meets minimum salary or skill thresholds — always confirm sponsorship eligibility with the recruiter.

The job posting also states: “✈️ Relocation support and visa sponsorship where applicable”

Verification category
Employer on official sponsor register
Role category
ML / AI
Last verified
2026-10-25
First indexed
2026-10-24
Posted date
2026-10-16
ATS / Feed source
Ashby job board

Role Description (Excerpt)

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 ADAS Team Wayve's ADAS engineering teams build the perception and intelligence that power driver assistance in real-world driving. We work end-to-end, from creating high-quality training data, to developing and evaluating CV/3D perception models, to iterating quickly based on performance gaps. The team mixes "online" (on-car, latency/compute constrained) and "offline" (heavier, large-scale data generation) work, with a strong focus on measurable impact and shipping. 🧠 Your day-to-day - Train, debug, and improve computer vision and 3D perception models, iterating based on clear evaluation signals - Work across the full ML lifecycle: data, training, evaluation, and iteration - Partner with the team to decide what to tackle next, based on where the system is underperforming - Build scalable data pipelines, including auto-labelling and pseudo-labelling, to accelerate model development 🧩 What you'll be working on: - Core ADAS perception capabilities such as detection, classification, and instance segmentation, spanning lanes, objects, traffic signs, and traffic lights - End-to-end approaches that let the model act on the world directly, rather than…

Excerpt only — read the full requirements and apply directly on Wayve's career page. We do not process applications.