Staff Machine Learning Engineer, AV Core
Core
Shape end-to-end driving model safety and reliability by defining what the model must understand, turning research into trained capabilities, and ensuring adoption across core and product engineering.
Role type
Staff Machine Learning Engineer (Autonomous Vehicles)
Builds
End-to-end AV 2.0 models, collision avoidance, scene understanding, and robustness capabilities for automated driving systems.
Domain
Autonomous driving / Embodied AI / Computer Vision
Deliverable
production ML models
Required skills
ML engineering, Python, C++, CUDA, PyTorch, transformer-based architectures, multimodal models, vision-language models, vision-language-action models, multi-stage training, shared representations, staff-level technical leadership, research direction setting, cross-functional collaboration, mentoring
Preferred skills
Autonomous vehicles or robotics deployment, 3D scene understanding, reward modelling, behaviour modelling, model introspection, interpretability, redundant/fallback architectures, safety-critical systems, large-scale training infrastructure, agentic workflows
Technologies
PyTorch, C++, CUDA, Python
Responsibilities
Drive Core Model Safety roadmap themes owning the full lifecycle from research to offline/online experiments to technology transfer; Train and deploy end-to-end AV 2.0 models on global fleet using large-scale diverse data; Build high-value open-loop and closed-loop evaluations for core capabilities and representation learning; Align priorities and learn from the organisation with AV Core, Evaluation, and Product Engineering on roadmaps and failure modes; Maintain awareness of the wider business context including division and company priorities
Seniority
Staff, hands-on IC with technical leadership
