Control Engineer

Job description

About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The Role We’re seeking an exceptional Engineer to join our Germany-based Application Engineering team, focused on localising and advancing Wayve’s autonomous driving technology for the German market. You’ll play a pivotal role in integrating, validating, and optimising our MPC-based trajectory controller and AI software stack on new vehicle platforms ensuring safe, reliable, and high-performance driving in diverse real-world conditions. This is a unique opportunity to work at the intersection of controls, systems integration, and applied machine learning , helping expand our AV capabilities across new operational domains while collaborating closely with robotics, ML, and vehicle engineering experts. Key Responsibilities Integrate and validate Wayve’s AI software stack and MPC-based trajectory controller on customer hardware and vehicle platforms. Maintain and enhance the controller (coupled with ML-driven trajectory generation) to improve performance, stability, and reliability across different vehicles and environments. Establish and advance control and integration methods for ML-coupled systems, ensuring robustness and scalability across operational domains. Test and optimise system behaviour in challenging driving scenarios — from highways to urban settings and adverse weather conditions. Develop and refine simulation and evaluation pipelines to guarantee real-world optimality and…