Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Machine Learning Engineer role.
Rezi rewrites your resume against Wayve's job description. Free.
Tailor your resume to this Machine Learning Engineer role.
Rezi rewrites your resume against Wayve's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Machine Learning Engineer posting at Wayve — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Machine Learning Engineer posting at Wayve — free, in seconds.
About the Role
Lead critical initiatives that push the frontier of model-based autonomous driving, focusing on core driving performance and feature-level intelligence. Design and deliver ML-driven behaviors that scale from assisted to autonomous driving, spanning model architecture, data pipelines, evaluation frameworks, and real-world deployment. Collaborate with AI Platform, Simulation, Robot SW, and Model Release teams to build performant, adaptable, and production-ready systems.
Responsibilities
- Develop and improve end-to-end driving models with state-of-the-art performance, robustness, and generalization.
- Lead projects on personalized and collaborative driving, including behavior conditioning, comfort tuning, and user alignment.
- Build evaluation pipelines and metrics for both closed-loop and open-loop driving performance and product readiness.
- Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development.
- Influence architecture choices, training methodologies, and deployment pathways for production-scale learning systems.
- Collaborate cross-functionally across various teams to ensure integration and iteration velocity.
- Mentor senior engineers and shape the long-term technical direction across Autonomy.
Requirements
- Extensive and proven track record of shipping deep learning systems to production.
- Expert in deep learning (esp. sequential models, control, planning, or perception).
- Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices.
- Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components.
- Ability to lead technical initiatives across teams, drive alignment, and mentor engineers.
- Prior work in autonomous driving, imitation learning, or trajectory prediction.
- Familiarity with personalization, human behavior modelling, or driver intent inference.
- Experience integrating ML systems into production hardware or multi-agent simulation.
Skills
- Deep learning
- Sequential models
- Control
- Planning
- Perception
- Python
- C++
- CUDA
- PyTorch
- Software engineering
- Real-time systems
- Robotics
- Simulation
- Vehicle-in-the-loop
- Autonomous driving
- Imitation learning
- Trajectory prediction
- Personalization
- Human behavior modelling
- Driver intent inference
- ML systems integration
- Production hardware integration
- Multi-agent simulation
Location
- Japan
Work Type
- Full-time
- Hybrid
Experience Level
- Senior