Senior Machine Learning Engineer, ADAS
Salary not listed • London, United Kingdom • Full-time
Posted 15d ago
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 is within the ADAS engineering team, which focuses on the perception and intelligence powering driver assistance systems. The team works across the full ML lifecycle, from data creation to model development and evaluation, with a strong emphasis on measurable impact and shipping production-ready features. You will contribute to core ADAS perception capabilities and end-to-end approaches that allow models to act directly on the world, improving real-world driving performance.
Responsibilities
- Train, debug, and improve computer vision and 3D perception models based on evaluation signals.
- Manage the full ML lifecycle, including data preparation, model training, evaluation, and iteration.
- Collaborate with the team to prioritize development efforts based on system performance gaps.
- Develop scalable data pipelines, incorporating auto-labelling and pseudo-labelling techniques.
- Work on core ADAS perception tasks like detection, classification, and instance segmentation for various road elements.
- Develop end-to-end perception models that directly influence vehicle actions.
- Contribute to online perception systems for in-car, low-latency deployment.
- Engage in offline perception work using diverse data sources to enhance data quality and model coverage.
- Build and maintain the 'data flywheel' for accelerating perception task iteration through automated labeling.
Requirements
- Experience building and shipping CV-focused deep learning systems with a strong applied ML engineering focus.
- Familiarity with 3D perception concepts or pipelines (e.g., LiDAR, multi-view geometry, tracking, 3D reconstruction).
- Proficiency in owning work end-to-end, including evaluation and large-scale dataset generation.
- Ability to solve pragmatic problems under real product constraints.
- Passion for improving real-world driving performance through enhanced perception.
- Experience in the automotive domain is a plus.
Benefits
- Salaries benchmarked against the market annually
- Meaningful equity
- Relocation support
- Visa sponsorship
- Hybrid working model
- Core working hours
- Opportunity to work hands-on in vehicle workshops and labs
- Learning and development budgets
- Support for training and conferences
- Comprehensive health insurance
- Dental insurance
- Enhanced maternity and paternity leave
- Retirement or pension contributions
- Access to therapists
- Wellbeing partner discounts