Wayve
AI
StaffMachineLearningEngineer,AVCore
Neural analysis suggests this role is
optimal for Lead candidates.
“Staff Machine Learning Engineer, AV Core at Wayve. Skills: Machine Learning, Autonomous Driving, Model Safety, Python. Drive Core Model Safety roadmap. Own full lifecycle from research”
What You'll Achieve.
Enhance usability of automated driving systems; Enhance safety of automated driving systems; Accelerate transition to automated driving; Ensure safety and reliability of driving model; Turn understanding into trained capabilities; Turn understanding into clear evidence; Turn understanding into adoption on shared backbone
Industry & Context.
Pathfinding in ambiguous problems; Embrace uncertainty; Lean into complex challenges
What They're Looking For.
Must Have
5+ years in ML engineering, Proficient in Python, Proficient in C++, Proficient in CUDA, Proficient in PyTorch, Solid foundation in software engineering practices, Hands-on experience with transformer-based architectures, Hands-on experience with multimodal architectures, Hands-on experience with vision-language models (VLM), Hands-on experience with vision-language-action models (VLA), Hands-on experience training shared representations with multiple tasks or objectives, Staff-level technical leadership, Research-literate and pragmatic, Setting direction, Raising the bar, Leading cross-functional work without formal line management
Nice to Have
Prior experience in autonomous vehicles, Prior experience in robotics, Hands-on deployment on physical systems, Closed-loop validation on physical systems, Experience in 3D scene understanding, Experience in representation learning for geometric perception, Experience in representation learning for semantic perception, Experience in large-scale semantic enrichments, Experience in reward modelling, Experience in behaviour modelling, Experience in model introspection, Experience in interpretability, Experience with redundant architectures, Experience with fallback architectures, Experience with safety-critical systems, Experience across foundations/pretraining, Experience across applied engineering, Experience with large-scale training infrastructure, Experience with agentic workflows
What You'll Do.
Drive Core Model Safety roadmap
Own full lifecycle from research
Train end-to-end AV 2.0 models
Deploy end-to-end AV 2.0 models
Validate capabilities
Improve generalisation
Build high-value evaluations
Align priorities with organisation
Learn from organisation
Mentor others on team
Maintain awareness of business context
How You'll Work.
Team & Collaboration
Work with partners in research; Work with partners in simulation; Work with partners in evaluation; Work with partners in applied engineering; Align priorities with AV Core; Align priorities with Evaluation; Align priorities with Product Engineering; Collaborate on roadmaps; Collaborate on failure analysis; Lead cross-functional work
Full Job Description
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 Staff Machine Learning Engineer on Wayve’s Core Model Safety team in AV Core, you will help shape what our end-to-end driving model must understand to be safe and reliable in the real world - and turn that into trained capabilities, clear evidence, and adoption on the shared backbone across core and product engineering. The Core Model Safety team builds foundational capabilities for assisted and automated driving - collision avoidance, scene understanding, model understanding, and robustness under failure. You will work in a focused, high-impact senior team with strong ownership, access to large-scale training and fleet data, and close partners in research, simulation, evaluation, and applied engineering. Key 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 our global fleet, using large-scale, diverse data to validate capabilities and i
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