Adas Feature Engineer

Wayve Wayve · Robotics · Tokyo, Japan · Product & Delivery

This role focuses on building the application-layer software for ADAS features, integrating Wayve's AI capabilities with vehicle behavior. The engineer will develop C++ feature logic, validation tools, and system behaviors, working closely with ML, product, and vehicle integration teams to translate model outputs into reliable ADAS features for real-world vehicle environments. The role involves debugging, tuning, validation, and collaboration across various engineering and product teams.

What you'd actually do

  1. Design, implement, and maintain C++ application software for ADAS and active-safety-related vehicle features.
  2. Build feature-level logic on top of AI / ML outputs, including validation, feasibility checks, state machines, fallback behaviours, and safety-aware decision logic.
  3. Work with ML engineers to understand model outputs, limitations, failure modes, and how these translate into vehicle behaviour.
  4. Use logs, simulation, replay, and vehicle testing to debug, tune, and validate feature behaviour.
  5. Define and improve metrics, test cases, and validation strategies for ADAS feature performance, robustness, and quality.

Skills

Required

  • C++
  • ADAS
  • autonomous driving
  • robotics
  • vehicle software
  • active safety
  • real-world testing
  • simulation
  • replay
  • logs
  • prototype vehicle debugging
  • vehicle behavior reasoning
  • sensor/model input reasoning
  • timing reasoning
  • failure mode reasoning
  • feature-level decision logic
  • cross-functional collaboration
  • problem-solving
  • pragmatic engineering trade-offs
  • quality mindset
  • testable software
  • maintainable software
  • data validation

Nice to have

  • AEB
  • ISA
  • AES
  • ACC
  • lane keeping
  • collision avoidance
  • trajectory validation
  • automotive OEM experience
  • Tier 1 supplier experience
  • autonomous driving company experience
  • robotics company experience
  • vehicle technology startup experience
  • ROS
  • Linux
  • Bazel
  • CMake
  • Docker
  • QNX
  • protobuf
  • MCAP
  • CAN
  • calibration
  • vehicle logging systems
  • vehicle test tracks
  • public-road testing
  • HIL/SIL
  • scenario-based testing
  • NCAP-style validation
  • CANoe
  • Vector tools
  • MicroAutoBox
  • Japanese language skills

What the JD emphasized

  • 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.

Other signals

  • Develop C++ feature logic, validation tools, and system behaviours that allow AI-native driving technology to operate robustly in real-world vehicle environments.
  • 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.