Staff Machine Learning Engineer (AV Core)

Join Wayve, a leading company in the autonomous vehicle industry. As a Staff Machine Learning Engineer on the Core Model Safety team, you will play a crucial role in shaping the safety and reliability of our end-to-end driving model. You will work in a high-impact senior team, driving the Core Model Safety roadmap and training and deploying AV models on our global fleet. This position offers competitive compensation, private healthcare, paid time off, mental health resources, and opportunities for learning and development.

• Conduire les thèmes de la feuille de route de la sécurité du modèle de base, en possédant l'ensemble du cycle de vie, de la recherche aux expériences hors ligne/en ligne.
• Former et déployer des modèles AV 2.0 de bout en bout sur notre flotte mondiale, en utilisant des données diversifiées à grande échelle.
• Construire des évaluations ouvertes et fermées de haute valeur pour les capacités de base et l'apprentissage de la représentation.
• 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
• 5+ years in ML engineering, including pathfinding in ambiguous problems - from scoping and evals to establishing a direction (and knowledge transfer) for others to build on
• Hands-on experience training shared representations with multiple tasks or objectives (multi-stage or joint training), including real trade-offs across data and losses
• Staff-level technical leadership: research-literate and pragmatic, setting direction, raising the bar, and leading cross-functional work without formal line management
• Hands-on experience with transformer-based and multimodal architectures, including vision-language models (VLM), vision-language-action models (VLA), or equivalent
• 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
• Experience across foundations/pretraining and applied engineering teams; large-scale training infrastructure and/or agentic workflows
• Experience with redundant or fallback architectures, safety-critical systems
• Experience in reward modelling, behaviour modelling, model introspection, and/or interpretability
• Prior experience in autonomous vehicles or robotics with hands-on deployment and closed-loop validation on physical systems
• Experience in 3D scene understanding and representation learning for geometric and semantic perception, large-scale semantic enrichments