Machine Learning Engineer, App SW
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
Wayve is hiring a Machine Learning Engineer for its Application Engineering team. The role focuses on developing production-scale learning systems for autonomous driving, including driving models, personalized and collaborative driving behaviors, evaluation frameworks, data development, and deployment. The position is based in Sunnyvale or Detroit under Wayve's hybrid working policy.
Requirements
- Extensive proven experience shipping deep learning systems to production.
- Expertise in deep learning, particularly sequential models, control, planning, or perception.
- Proficiency in Python and relevant languages such as C++ and CUDA, plus ML frameworks including PyTorch.
- Strong software engineering foundations.
- Experience with real-time systems or robotics, ideally involving simulation- or vehicle-in-the-loop components.
- Ability to lead technical initiatives across teams, drive alignment, and mentor engineers.
- Experience in autonomous driving, imitation learning, or trajectory prediction is desirable.
- Familiarity with personalization, human behavior modeling, driver intent inference, production hardware integration, or multi-agent simulation is desirable.
Responsibilities
- Develop and improve end-to-end driving models for performance, robustness, and generalization.
- Lead projects involving personalized and collaborative driving, behavior conditioning, comfort tuning, and user alignment.
- Build evaluation pipelines and metrics for closed-loop and open-loop driving performance and product readiness.
- Curate and mine real-world and synthetic data for scenario diversity, coverage, and feature development.
- Influence architecture, training methodologies, and deployment pathways for production-scale learning systems.
- Collaborate across AI Platform, Simulation, Robot SW, and Model Release teams.
- Mentor senior engineers and shape long-term technical direction across Autonomy.
Benefits
- Salary range of $283,500 to $381,600 per year.
- Competitive equity package.
- Hybrid working policy combining office and workshop time with work from home.
- Core working hours with schedule flexibility for the employee and team.