1 day ago
London, United KingdomMid Level
Responsibilities
- Train, debug, evaluate, and improve computer vision and 3D perception models.
- Develop ADAS perception capabilities for lanes, objects, traffic signs, and traffic lights.
- Build scalable data pipelines, including auto-labelling and pseudo-labelling workflows.
- Develop offline tracking and 3D reconstruction pipelines to generate labelled datasets.
- Work across data, training, evaluation, and iteration while targeting measurable real-world driving improvements.
- Contribute to online, latency- and compute-constrained in-vehicle models or offline large-scale data-generation models.
Requirements
- Experience building and shipping computer-vision-focused deep learning systems.
- Strong applied machine learning engineering experience beyond research-only work.
- Experience with 3D perception concepts or pipelines, such as LiDAR, multi-view geometry, tracking, or 3D reconstruction.
- Ability to own work end-to-end, including evaluation and dataset generation.
- Comfort working with real product constraints and pragmatic problem-solving.
- Passion for autonomy and willingness to learn; candidates do not need to meet every listed qualification.
Benefits
- Hybrid working with in-person collaboration and remote work across Wayve hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg.
- Relocation support and visa sponsorship where applicable.
- Hands-on work in vehicle workshops and labs, with core hours.
- Learning and development budgets for training, conferences, and growth.
- Health insurance, dental coverage, enhanced maternity and paternity leave, retirement or pension benefits where applicable, therapy access, wellbeing partnerships, and team socials.
- Meaningful equity and market-benchmarked salaries; compensation figures are not specified.
Categories
ML EngineeringRobotics
