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 Engineering Teams
You’ll join Wayve’s Product & Delivery (P&D) organization, working within the Sensor Architecture team to help define and integrate the sensor systems behind our end-to-end autonomy stack.
The team works across the full sensor suite, with particular depth in camera systems, while also shaping radar, lidar and other sensing topics across customer and vehicle programs.
You’ll work closely with Wayve’s hardware and software teams, OEMs, Tier 1s and sensor suppliers, helping connect what sensors can physically deliver with how the Wayve AI Driver performs in real-world driving conditions.
This role sits at the intersection of sensor technology, vehicle integration and autonomous-driving performance, with responsibility for taking defined sensor topics from analysis through to clear, data-backed technical recommendations.
🧠 Your day-to-day
You’ll help translate driving use cases, ODD requirements and product constraints into clear sensor-system requirements and measurable KPIs such as coverage, field of view, resolution, detection range and latency.
A significant part of your work will focus on camera systems. You’ll contribute to camera concepts, module and sensor selection, variants, field of view, placement and integration requirements across different vehicle platforms.
You’ll evaluate and help tune image quality across areas such as exposure, HDR, ISP behaviour, LED flicker, low-light performance and image artefacts, working closely with Wayve’s hardware team and camera / ISP suppliers.
You’ll also work directly with OEMs and Tier 1s on camera mounting and vehicle-integration requirements, including position, alignment and tilt tolerances, mount rigidity, windshield and cover-glass effects, occlusion, heating and cleaning, synchronisation and calibration assumptions.
Beyond cameras, you’ll contribute to radar and lidar topics, supporting requirements definition, sample evaluation and integration discussions around areas such as mounting, radome and fascia effects, calibration and interference.
You’ll analyze fleet, replay and validation data to understand gaps between expected and observed sensor behaviour, define test requirements with the hardware team, review results and recommend next steps.
The role also includes hands-on work in the lab and on vehicles, supporting sensor bring-up and integration debugging when needed, as well as using Python to automate analysis and reporting.
🧩 What you’ll be working on:
- Defining sensor-system requirements and quantitative KPIs derived from driving use cases, ODD and product constraints.
- Developing camera-system concepts across sensor/module selection, variants, FOV and placement.
- Evaluating camera image quality, including exposure, HDR, ISP, LED flicker, low-light performance and common image artefacts.
- Defining camera mounting and vehicle-integration requirements for OEMs and Tier 1s.
- Ensuring sensor characteristics, installation assumptions and calibration requirements remain consistent across development and production programs.
- Analyzing fleet, simulation, replay and validation data to understand sensor performance and its impact on system KPIs.
- Defining test requirements, reviewing results and supporting hands-on lab and vehicle testing.
- Supporting sensor bring-up and hardware/software integration debugging.
- Working directly with camera, radar and lidar suppliers on technical requirements, sample evaluation and integration constraints.
- Supporting radar integration topics including mounting, radome/fascia effects and interference.
- Supporting lidar and other sensing technologies such as ultrasonics where required.
- Answering technical camera and sensor questions from customers and partners.
- Maintaining sensor requirements, imaging guidelines, test specifications and technical recommendations.
- Automating sensor-data analysis and reporting using Python.
- Helping identify production and manufacturability constraints early as customer programs move from development toward production.
🙌 You should apply if:
- 5+ years, of hands-on experience in automotive camera, radar or lidar engineering.
- You have delivered technical work on automotive programs from requirements through integration, validation and verified results.
- You have strong knowledge of camera systems, including image sensors, exposure, HDR, ISP pipelines, calibration and image artefacts.
- You have practical experience with camera integration, image quality, sensor characterisation or ADAS sensor validation.
- You have working knowledge of radar and/or lidar fundamentals and their vehicle-integration constraints, and can lead first-level technical discussions with suppliers.
- You have experience defining camera mounting and integration requirements with OEMs or Tier 1s, including alignment tolerances, windshield or cover-glass effects, occlusion and mount rigidity.
- You have used measurement and data analysis to make technical decisions, including image-quality evaluation using standard charts, tools and methods.
- You are comfortable working across both hardware and software teams and directly with suppliers, OEMs and customers.
- You can use Python or MATLAB for engineering analysis, automation and reporting.
- You can write clear requirements, test specifications and concise, data-backed recommendations.
- You enjoy working independently within a defined technical area and taking ownership from analysis through recommendation.
- You are curious about how sensor behaviour affects autonomous-driving performance and are interested in broadening your expertise across camera, radar and lidar.
Experience with production ADAS or AV programs, mass-production sensor integration, ML-based perception, fleet-data analysis, replay-based validation, radome/fascia evaluation, IEEE P2020 concepts, ultrasonic sensors, SerDes, sensor configuration or synchronisation would be a strong advantage.
🌱 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.
More 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.
How we work 💻- 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:
Our process is clear and respectful of your time:
- Initial call / recruiter screen
- Competency Interview
- Deep-dive technical interviews
- Final interview:
We’ll always explain the format and work around your availability.
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
A quick, honest note before you apply.
Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.
If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.
For more information visit Careers at Wayve. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/
DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
