ADAS Feature Engineer, Application Software

Overview

In this role you will design and implement C++ software that enables AI-driven ADAS features to operate safely in real vehicles. You’ll translate model outputs and vehicle data into robust, testable behaviours with validation and safety-focused logic. You will work closely with ML, product, systems, and vehicle teams to address real-world constraints and edge cases. This position offers hands-on tuning and debugging across logs, simulation, replay, and field testing, with a strong emphasis on quality and measurable performance.

Pay / Benefits

• salary benchmarked against market
• equity
• relocation and visa sponsorship
• hybrid working model
• learning and development budgets
• health insurance and dental, enhanced maternity/paternity leave, retirement plan

Responsibilities

• Design, implement, and maintain C++ software for ADAS and active-safety features
• Develop feature-level logic on top of ML outputs, including validation, state machines, and safety-aware decisions
• Collaborate with ML engineers to interpret model outputs and limitations for vehicle behaviour
• Use logs, simulation, replay, and vehicle testing to debug and tune feature behaviour
• Define metrics, test cases, and validation strategies for ADAS performance and robustness
• Work with product, systems, vehicle integration, and OEM teams to translate requirements into solutions
• Support field testing and iterative development, investigating issues and gaps
• Contribute to software architecture, code quality, tooling, and engineering practices

Key requirements

• Strong C++ software engineering experience in production or safety-relevant systems
• Hands-on ADAS/autonomous driving/robotics/vehicle software experience
• Practical understanding of vehicle feature development including testing, simulation, logs, and debugging
• Ability to reason about vehicle behaviour, sensor inputs, timing, and failure modes in feature decisions
• Cross-functional collaboration with ML, perception, planning, controls, vehicle integration, or systems engineering
• Strong problem-solving and pragmatic trade-off thinking under ambiguity
• Quality mindset with testable, maintainable software and data-driven validation

• strong collaboration
• problem-solving
• pragmatic decision-making
• C++
• ADAS / autonomous driving domain knowledge
• ROS

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