Senior Machine Learning Engineer - AV Core
Wayve is a London-headquartered embodied-AI company developing and licensing mapless, vehicle-agnostic driving software for assisted, automated, and robotaxi applications.
About Wayve
Wayve Technologies Ltd. develops the Wayve AI Driver, an end-to-end, data-trained software platform that runs on onboard vehicle compute and native sensors. It is designed for OEM integration across L1 driver assistance through L4 automated driving, without HD maps.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead large-scale data enrichment, curation, and rare-event mining for machine learning systems. You will build and train out-of-distribution detection mechanisms, shape architecture across model engineering and infrastructure, and improve the efficiency of machine learning and operations systems.
Requirements
- Experience with real-world deployed machine learning systems
- Python
- PyTorch
- Software engineering practices
- Experience building machine learning training and evaluation systems
- Machine learning operations and infrastructure
- Distributed computing
- Large-scale inference
- Senior-level technical ownership and cross-functional collaboration
- Autonomous vehicle or robotics deployment and closed-loop validation
- Rare-event mining generation or evaluation using simulation and fleet data
- Cloud monitoring dashboards logging and real-time alerts
- Transformer architectures
- Multimodal architectures
- Vision-language model
- Vision-language-action model
- C++
- CUDA
- Distributed training
- Performance optimization
Responsibilities
- Lead large-scale data enrichment collaborations
- Build workflows for data enrichment curation and hard-event mining
- Design and train out-of-distribution detection mechanisms
- Shape architecture across model engineering infrastructure compute and data
- Improve the efficiency of machine learning and operations systems
Benefits
- Hybrid working