wayve - Staff Robotics Engineer, AV Core

• Set the technical strategy and roadmap for fault detection and fallback, including its behavioural scope, operating envelope, system interfaces, and measurable acceptance criteria • Design and train fault detection mechanisms using the methods best supported by evidence, to enable robust driverless operation • Collaborate across functions and expertise areas, including machine learning, inference optimisation, and software engineering • Lead integration into the shared driving stack, align technical decisions across teams, and raise the bar through architecture reviews, mentoring, and clear communication of risks, trade-offs, and evidence • Use your judgement and expertise to improve the overall robustness of the robot system, beyond just fault detection and fallback • 🧩 What you'll be working on: • Fault detection and fallback systems that let the vehicle respond safely when something goes wrong, from strategy through to deployment on the car • Collision avoidance, model understanding, and robustness under failure: the foundational capabilities this team owns for assisted and automated driving • Fault detection methods chosen on the strength of evidence, built to hold up under real driverless operation • Integration into the shared driving stack, working closely with machine learning, inference optimisation, and software engineering partners • Large-scale training and fleet data, with close partners in research, simulation, evaluation, and applied engineering • 👤 You should apply if: • Proficient in developing, implementing, and troubleshooting robotics solutions, backed by practical, real-world experience • A track record of staff-level technical leadership: setting direction for ambiguous programmes, aligning multiple teams, and carrying work from research through production deployment • Strong technical judgement and communication, able to make safety-relevant trade-offs explicit and lead without relying on formal authority • Comfortable working in Python and C++ for robotics • Experience deploying and maintaining fleets of robots or vehicles at scale under real-world conditions • Bonus if you've built tooling to triage and debug robotic systems, or set up cloud-based monitoring for large-scale fleets • Familiarity with embedded or real-time systems, or hands-on machine learning and inference optimisation experience, is a plus • 🌱 Not ticking every box? That's totally okay! If you're passionate about autonomy and keen to learn, we encourage you to apply even if you don't meet every requirement.