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ADAS Feature Engineer, App SW

in 10115, Berlin, Berlin, Deutschland
Unternehmen: Wayve
Vollzeit position
Verfasst am 2026-10-11
Berufliche Spezialisierung:
  • Software Entwicklung
    Künstliche Intelligenz Ingenieur, Softwaretester, Eingebettete Software ingenieur, Maschinelles Lernen
Gehalts-/Lohnspanne oder Branchenbenchmark: 70000 - 110000 EUR pro Jahr EUR 70000.00 110000.00 YEAR
Stellenbeschreibung

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 Feature Engineering Team

We’re seeking an exceptional Feature Engineer to join our Germany-based team within the Application Engineering org, focused on localising and advancing Wayve’s autonomous driving technology for the German market. This is a unique opportunity to play a hands‑on role in shaping our AV capabilities in Germany from the ground up.

What you’ll be working on

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.

Your day-to-day
  • 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.
You should apply if

Essential

  • 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.

Desirable

  • 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…
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