ADAS Feature Engineer

Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. 

In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  

Make Wayve the experience that defines your career!  

We are looking for an ADAS Feature Engineer to help build the application-layer software that connects Wayve’s AI capabilities to real vehicle behaviour. This role sits at the intersection of AI, vehicle systems, active safety, and product delivery: you will develop C++ feature logic, validation tools, and system behaviours that allow AI-native driving technology to operate robustly in real-world vehicle environments. You will work closely with machine learning, product, vehicle integration, and systems teams to turn model outputs and vehicle data into reliable, testable, and customer-relevant ADAS features.

• →Design, implement, and maintain C++ application software for ADAS and active-safety-related vehicle features.
• →Build feature-level logic on top of AI / ML outputs, including validation, feasibility checks, state machines, fallback behaviours, and safety-aware decision logic.
• →Work with ML engineers to understand model outputs, limitations, failure modes, and how these translate into vehicle behaviour.
• →Use logs, simulation, replay, and vehicle testing to debug, tune, and validate feature behaviour.
• →Define and improve metrics, test cases, and validation strategies for ADAS feature performance, robustness, and quality.
• →Collaborate with product, systems, vehicle integration, and OEM-facing teams to translate requirements and real-world constraints into engineering solutions.
• →Support field testing and iterative development, including investigation of vehicle issues, edge cases, and performance gaps.
• →Contribute to software architecture, code quality, tooling, and engineering practices for feature development.

In order to set you up for success as an ADAS Feature Engineer at Wayve, we’re looking for the following skills and experience:

• Strong C++ software engineering experience, ideally in production or safety-relevant systems.
• Hands-on experience in ADAS, autonomous driving, robotics, vehicle software, active safety, or closely related domains.
• Practical understanding of vehicle feature development, including real-world testing, simulation, replay, logs, or prototype vehicle debugging.
• Ability to reason about vehicle behaviour, sensor/model inputs, timing, failure modes, and feature-level decision logic.
• Experience working cross-functionally with teams such as ML, perception, planning, controls, vehicle integration, product, or systems engineering.
• Strong problem-solving skills and the ability to make pragmatic engineering trade-offs under ambiguity.
• A quality mindset, with experience writing testable, maintainable software and using data to validate behaviour.

• Experience with ADAS features such as AEB, ISA, AES, ACC, lane keeping, collision avoidance, trajectory validation, or active safety systems.
• Experience at an automotive OEM, Tier 1 supplier, autonomous driving company, robotics company, or vehicle technology startup.
• Familiarity with ML or AI-based autonomy systems, including how model outputs are consumed by downstream software.
• Experience with ROS, Linux, Bazel, CMake, Docker, QNX, protobuf, MCAP, CAN, calibration, or vehicle logging systems.
• Experience with vehicle test tracks, public-road testing, HIL/SIL, scenario-based testing, or NCAP-style validation.
• Familiarity with tools used in automotive development and testing, such as CANoe, Vector tools, MicroAutoBox, or similar.
• Japanese language skills are beneficial but not required.