Tech Lead, ML Engineer - AV Product engineering

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

As a Tech Lead, Machine Learning Engineer within Wayve’s AV Product Engineering team, you will lead the navigation workstream for our end-to-end autonomous driving system - spanning L2+, L3, and robotaxi products. This is a rare opportunity to own your work from model training all the way through to deployment in production vehicles, with full visibility into the entire pipeline. Joining a small, high-impact team, you will set the technical direction for navigation ML and have meaningful scope for growth as the team expands.

Key Responsibilities

• Lead the navigation workstream, including route planning, rerouting, and driving across L2+, L3, and robotaxi products.
• Train and deploy end-to-end models for navigation and driving features, owning the full lifecycle from model training through to vehicle integration and production deployment.
• Define the roadmap and technical vision for navigation ML within the AV Features team, helping shape the direction of L2+ driving features.
• Collaborate closely with the Evaluation, Robot Software, and Data Platform teams to iterate rapidly and improve model performance.
• Leverage closed-loop and open-loop evaluation frameworks to measure driving quality and validate production readiness.
• Mentor and support junior engineers on the team and shape the long-term technical direction.

About you

Essential

• 7+ years of ML engineering experience with a strong track record of shipping deep learning systems to production.
• Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices.
• Hands-on experience with transformer-based and multimodal architectures, including vision-language models (VLM), vision-language-action models (VLA), or equivalent.
• Demonstrated ability to train and deploy end-to-end ML models for production systems.
• Strong understanding of end-to-end learning approaches for driving, embodied AI, or related domains.
• Ability to take full ownership of a technical workstream - driving it from research and experimentation through to production deployment.

Desirable

• Prior work in autonomous driving, imitation learning, or trajectory prediction. Or background in the AV industry, ideally from a perception, planning, controls, or evaluation team.
• Experience with closed-loop simulation and open-loop evaluation for autonomous driving or robotics systems.
• Familiarity with navigation problems, route planning, or multi-modal sensor fusion.
• Research publications in relevant areas (machine learning, robotics, computer vision) - less critical than strong applied production experience.