Machine Learning Engineer, Application Software
$312k - $351k • Sunnyvale, California USA • Full-time
Posted 28d ago
Job Location
Sunnyvale, California USA
Also open in Tokyo, Japan
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. This role focuses on advancing model-based autonomous driving, improving core driving performance, and developing intelligent features. You will lead critical initiatives to design and deliver ML-driven behaviors that scale from assisted to autonomous driving, working across model architecture, data pipelines, evaluation frameworks, and real-world deployment. You will collaborate closely with AI Platform, Simulation, Robot Software, and Model Release teams to build performant, adaptable systems ready for production, while helping shape the long-term technical direction across Autonomy.
Responsibilities
- Develop and improve end-to-end driving models, enhancing performance, robustness, and generalization.
- Lead technical initiatives in personalized and collaborative driving, including behavior conditioning, comfort tuning, and alignment with user preferences.
- Build evaluation pipelines and metrics to assess driving performance and product readiness.
- Curate and mine real-world and synthetic data to improve scenario diversity and feature-specific development.
- Collaborate across engineering teams to integrate models, accelerate iteration, and support real-world deployment.
- Mentor senior engineers, drive technical alignment, and influence architecture, training, and deployment decisions.
Requirements
- Extensive, proven track record of shipping deep learning systems to production.
- Deep expertise in deep learning, particularly sequential models, control, planning, or perception.
- Proficiency in Python, experience with languages like C++ or CUDA, and confidence using ML frameworks, especially PyTorch.
- Strong foundation in software engineering practices and experience building reliable, maintainable ML systems.
- Experience with real-time systems or robotics, ideally including simulation-in-the-loop or vehicle-in-the-loop components.
- Ability to lead technical initiatives across teams, build alignment, and mentor engineers.
- Experience in autonomous driving, imitation learning, or trajectory prediction (preferred).
- Familiarity with personalization, human behavior modeling, or driver intent inference (preferred).
- Experience integrating ML systems into production hardware or multi-agent simulation (preferred).