Staff Machine Learning Engineer, Vision Models

In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.

5+ years in ML engineering, including training and shipping deep learning models in production, with pathfinding in ambiguous modelling problems from scoping through to a direction others build on.

Hands-on experience training modern computer vision models, including transformer-based and multimodal or VLM architectures for detection, segmentation, classification, or scene understanding, on camera and/or lidar sensor data.

Experience adapting or fine-tuning large pretrained or foundation models, and training shared representations across multiple tasks or objectives (multi-stage or joint training), including real trade-offs across data and losses.

Proficient in Python and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices and comfort with large-scale training.

Staff-level technical leadership: research-literate and pragmatic, setting direction, raising the bar, and leading cross-functional work without formal line management.

Able to measure your own models: comfortable defining and reading the metrics that show whether a model is genuinely improving.

Experience in 3D scene understanding and representation learning for geometric and semantic perception, including large-scale semantic enrichment of driving scenes.

Experience with offboard or offline modelling: auto-labelling, model distillation, temporal or world models, or other ways of exploiting compute that on-vehicle systems cannot.

Prior experience in autonomous vehicles or robotics with hands-on deployment and closed-loop validation on physical systems.

Experience with fleet-scale data and large-scale distributed training infrastructure.

This is a full-time role based in our office in Sunnyvale. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. The reasonably estimated salary for this role ranges from $370,040 to $407,330, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.