Who we are
Established in 2017, Wayve is a leader in autonomous vehicle technology, driven by breakthroughs in Embodied AI. Our intelligent, mapless, and hardware-agnostic technologies empower vehicles to navigate complex environments effortlessly.
Supported by prominent investors, Wayve is advancing the transition from assisted to fully automated driving, making transportation safer, more efficient, and universally accessible. Join our world-class, multinational team of engineers and researchers as we push the boundaries of frontier AI and autonomous driving, creating impactful technologies and products on a global scale
Where you will have an impact
- Translate strategy around expansion of operational design domain into requirements for vehicle dynamics modelling.
- Build and validate discrete-time models of our vehicles for use in offline simulation and repro tools.
- Find the right tradeoff between accuracy and performance for models used in our model-based trajectory controller, working with control engineers to get a clear picture of the requirements.
- Provide the evidence and support decision making around tradeoffs regarding accuracy and computational resource requirements.
Challenges you will own
- Own the roadmap for improvements to our vehicle dynamics models and ensure they continue to be aligned with our product roadmap.
- Driving reproducibility between offline simulation / repro tools from the vehicle model perspective, and communicating what is required to close the gap.
- Taking responsibility for writing and communicating requirements on vehicle platforms to be able to build sufficiently accurate models of the dynamics.
What you will bring to Wayve
Essential
- Experience developing high-fidelity simulation models of passenger and commercial road vehicles across a wide range of operating environments.
- Experience of deriving approximate models suitable for real-time control and/or estimation on embedded platforms by trading off fidelity and performance.
- Data-driven approaches (for example: machine learning / system identification) for modelling systems where the underlying physical parameters are not known.
- Strong in C++ or Python
Desirable
- Matlad/Simulink
What we offer you
- The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact
- Competitive compensation and benefits
- A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too
- A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day
- Benefits such as an : onsite chef, workplace nursery scheme, private health insurance, cycle scheme, therapy, yoga, two onsite bars, large social budgets
- This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We also operate core working hours so you can be where you need to be for family and loved ones too. Teams determine the routines that work best for them.
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of gender, gender identity, gender expression, race, sexual orientation, physical or mental disability, ethnicity, age or religious belief
DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
