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.