Staff Machine Learning Engineer, Vision Models
Core
Build computer vision and scene understanding models to measure Wayve Driver performance offline, adapting on-vehicle models and foundation models to assess coverage, mine rare events, and evaluate driving behavior.
Role type
Staff Machine Learning Engineer (Vision Models)
Builds
Offline scene understanding models for autonomous driving validation
Domain
Autonomous Vehicles / Computer Vision
Deliverable
production ML models
Required skills
Deep learning model training and shipping, transformer-based and multimodal/VLM architectures, foundation model adaptation and fine-tuning, multi-task/joint representation learning, Python and PyTorch, large-scale training, staff-level technical leadership, model benchmarking and metric definition
Preferred skills
3D scene understanding and representation learning, offboard/offline modelling techniques, autonomous vehicle deployment and closed-loop validation, fleet-scale data and distributed training infrastructure
Technologies
PyTorch, transformer architectures, VLMs, lidar, camera sensors
Responsibilities
Build, train, and fine-tune scene understanding models for offline measurement; improve model performance and diagnose failure modes across platforms and conditions; leverage offline compute advantages for higher capacity and temporal context; benchmark models and define quality bars to steer iteration; ensure benchmarked results are statistically defensible for safety cases; mentor team members and align priorities across cross-functional teams
Seniority
Staff, hands-on IC with technical leadership
