Senior 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 for rigorous evaluation.
Role type
Senior IC machine learning engineer (vision models)
Builds
Offline scene understanding models for driving performance measurement
Domain
Autonomous vehicles, computer vision, deep learning
Deliverable
production ML models
Required skills
training and shipping deep learning models in production, transformer-based and multimodal/VLM architectures for detection/segmentation/classification/scene understanding, adapting/fine-tuning large pretrained/foundation models, multi-stage or joint representation learning, Python and PyTorch, large-scale training, defining and analyzing model metrics
Preferred skills
3D scene understanding and representation learning, offboard/offline modelling (auto-labelling, distillation, temporal/world models), autonomous vehicles/robotics 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 advantages like higher compute and bidirectional temporal context; benchmark models and define quality bars to steer iteration; ensure benchmarked results are statistically defensible for validation pipelines; mentor team members and align priorities across sites
Seniority
Senior, hands-on IC
