Tech Lead Manager

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.  Join our world-class team as we tackle today’s most complex challenges and 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.   Make Wayve the experience that defines your career!

The Role

We’re looking for bold, talented, and creative people to join our journey in developing next-generation autonomous vehicles. We’re a growing start-up building our first cohort of engineers, and you can be at the heart of this!

We are looking for an experienced Tech Lead Manager to contribute technically while managing a small team. This hybrid role combines hands-on technical contributions with leadership responsibilities. You will work across our research team to build, integrate, test, and scale algorithms, tools, and machine learning solutions for autonomous driving.

About you

• 7+ years of ML engineering / applied science experience in an industrial research environment
• 2+ years of experience managing small teams
• Experience in GenAI, EfficientAI, LLMs, World Models, Reinforcement Learning, and Autonomous Driving
• Passion for working in a team on research ideas that have real-world impact
• Strong software engineering experience in Python and other relevant languages (e.g., C++ and CUDA)
• Several years of experience working on machine learning algorithms and systems
• A good grasp of machine learning literature
• Comfortable working with large quantities of image and video data
• Good insight into the practical aspects of training, validation, testing, and metrics for deep learning features/models
• MS, PhD or above in Machine Learning, Computer Science, Engineering, or a related technical discipline, or equivalent experience

Our offer:

• A position to shape the future of autonomous driving, and thus to tackle one of the biggest challenges of our time
• Immersion in a team of world-class researchers, engineers and entrepreneurs
• Competitive compensation and stock options
• On-site chef and bar, lots of fun socials, a workplace nursery scheme and more!
• Help relocating/travelling to London, with visa sponsorship
• Flexible working hours - we trust you to do your job well, at times that suit you and your team.

Wayve is built by people from all walks of life. We believe that it is our differences that make us stronger, and our unique perspectives and backgrounds that allow us to build something different. We are proud to be an equal opportunities workplace, where we don’t just embrace diversity but nurture it - so that we all thrive and grow.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

This is a full-time role based in our office in London, UK.  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 operate core working hours so you can determine the schedule that works best for you and your team.  

For more information visit Careers at Wayve. 

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.

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