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About our Engineering Teams
Wayveâs 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 âonlineâ (on-car, latency/compute constrained) and âofflineâ (heavier, large-scale data generation) work, with a strong focus on measurable impact and shipping.
Your day-to-day
Youâll train, debug, and improve computer vision and 3D perception models, and iterate based on clear evaluation signals. Youâll work across the full ML lifecycle (data â training â evaluation â 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.
What youâll be working on:
Youâll help deliver core ADAS perception capabilities such as detection, classification, and instance segmentation, with domain focus across lanes, objects, traffic signs, and traffic lights. Youâll contribute to offline pipelines like tracking + 3D reconstruction that let us back-propagate âknown goodâ 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:
- Youâve 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).
- Youâre comfortable owning work end-to-end, including evaluation and dataset generation.
- You enjoy pragmatic problem-solving, working under real product constraints.
- Youâre excited to improve real-world driving performance through better perception.
Reasons to use Rodeo
Iâm in my final year doing Economics and I donât know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer â it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) donât need a masters. Letâs look at the ones youâd be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet â that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant â 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
Youâve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon â deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme â client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right â and where to focus when applying.
đ Not ticking every box? Thatâs totally okay! If youâre passionate about autonomy and keen to learn, we encourage you to apply even if you donât meet every requirement.
More about Wayve:
đ 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. Wayveâs 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.


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How we work đ»- Locations & Flexible Working:
Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.
The Interview Process:
- Initial call / recruiter screen (30 mins)
- Competency Interviews (Programming and System Design 2 hours total)
- Deep-dive technical interviews (domain-specific interview: 1 hours total)
- Final interview: mission & values alignment (1 hour).
Weâll always explain the format and work around your availability.
Whatâs in it for you (Location dependant):
- đ° Salaries benchmarked against the market annually
- đ Meaningful equity, sharing in the ownership and long term success of Wayve
- âïž Relocation support and visa sponsorship where applicable
- â Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
- đ Learning and development budgets with support for training, conferences and growth
- đ©ș 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
âIt took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what Iâve been looking for.â
Jessica, London
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