Embedded Automotive Platforms, Staff Software Engineer

Job description

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 Engineering Teams The Embedded Automotive Platforms (EAP) group builds the software that connects Wayve’s AI Driver to the vehicle and its onboard systems. We develop the platform adaptation and integration layers that let our AI capabilities run reliably across different vehicles, hardware platforms and programmes. You’ll join a team working across Wayve’s internal fleets and customer programmes. Our work spans embedded software that resides between vehicle platforms, HMI and AI Driver, and the software interfaces that connect these capabilities to the AI Driver. We work closely with teams across autonomy, hardware, product and vehicle engineering to turn system requirements into robust, testable software. As a Staff Software engineer, you’ll own significant technical work from design through integration and validation. You’ll help shape how EAP software is structured, make sound engineering decisions in an evolving environment, and work with partner teams to deliver capabilities that operate reliably on real vehicles. 🧠 Your day-to-day - Design, build and maintain embedded software that integrates Wayve’s AI Driver with vehicle platforms and onboard systems. - Develop and evolve interfaces between AI capabilities, vehicle software and platform-specific components. - Work across areas such as inference integration, vehicle data, navigation, localisation, odometry, driver interaction and motion control interfaces. - Collaborate with engineers across autonomy, hardware, vehicle programmes and product to clarify requirements and resolve integration issues. - Take features from technical design through implementation, testing, vehicle integration and release. - Diagnose and resolve issues using simulation, hardware-in-the-loop, vehicle testing, logs and performance data. - Contribute to architecture and engineering practices that support reuse across vehicle platforms and programmes. - Use AI development tools where they can improve engineering productivity and software quality. 🧩 What you’ll be working on - Building and integrating software for current and future vehicle platforms, including internal development fleets and customer programmes. - Developing reliable interfaces and adaptation software between Wayve’s AI Driver and vehicle-specific systems. - Improving software quality, observability, performance and resilience in resource-constrained onboard environments. - Supporting the migration and evolution of capabilities across vehicle generations and hardware configurations. - Working with simulation and test teams to improve how embedded and vehicle-integrated software is validated. - Contributing to technical direction, reviewing designs and code, and helping raise engineering standards across the team. 🙌 You should apply if - Essential: a bachelor’s or master’s degree in Computer Science, Electrical, Automotive Engineering or a related technical discipline, or equivalent practical experience. - Essential: strong software engineering experience in modern C++, with a track record of delivering production-quality software. - Essential: experience developing embedded or systems software, ideally on Nvidia and Qualcomm platforms with Linux/QNX. - Essential: experience with Linux-based platforms. - Essential: experience with system architecture and designing software components, APIs or interfaces for complex systems. - Essential: strong understanding of software quality practices, including testing, debugging, code review and maintainability. - Essential: experience diagnosing problems across component or system boundaries. - Essential: ability to work with technical partners to clarify requirements and make progress in ambiguous situations. - Essential: clear communication and collaboration skills, including working across teams and locations. - Essential: a practical, ownership-minded approach, so you can take a complex problem from investigation through implementation and validation. - Desirable: experience in autonomous driving, automotive, robotics or another real-time, safety-related domain. - Desirable: familiarity with vehicle software, middleware, sensors, actuators or vehicle communication protocols. - Desirable: experience integrating machine-learning inference or other compute-intensive workloads on embedded hardware. - Desirable: familiarity with AV stack components like navigation, state estimation or driver-interaction systems. - Desirable: experience with simulation, hardware-in-the-loop testing or vehicle testing. - Desirable: familiarity with automotive software development processes, i