Machine Learning Engineer, ADAS

📋 Job Overview

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.

🏢 About Wayve

Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.

Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.

🎯 The Role

You’ll train, debug, and improve computer vision and 3D perception models, and iterate based on clear evaluation signals. You’ll work across the full ML lifecycle (data → training → evaluation → iteration), partnering with the team to decide what to tackle next based on where the system is underperforming. A meaningful portion of the role involves building scalable data pipelines (including auto-labelling / pseudo-labelling) to accelerate model development.

✅ Key Responsibilities

• Help deliver core ADAS perception capabilities such as detection, classification, and instance segmentation, with domain focus across lanes, objects, traffic signs, and traffic lights.
• Contribute to offline pipelines like tracking + 3D reconstruction that let us back-propagate “known good” labels through time and generate large labelled datasets.
• Depending on your strengths, you may lean more into online models that must run fast in-car, or offline models that improve data quality and coverage at scale.

🙌 You should apply if:

You’ve built and shipped CV-focused deep learning systems and can demonstrate strong applied ML engineering (not research-only). You have experience with 3D perception concepts or pipelines (e.g., LiDAR, multi-view geometry, tracking, 3D reconstruction) and you’re comfortable owning work end-to-end, including evaluation and dataset generation. You enjoy pragmatic problem-solving, working under real product constraints, and you’re excited to improve real-world driving performance through better perception.

Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.

🎁 Benefits

What’s in it for you (Location dependant):

💰 Salaries benchmarked against the market annually
📈 Meaningful equity, sharing in the ownership and long term success of Wayve
✈️ Relocation support and visa sponsorship where applicable
✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
📚 Learning and development budgets with support for training, conferences and growth
🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more

🛂 Visa & Eligibility

We offer visa sponsorship and relocation support where applicable.