2 months ago
Israel (city not specified)Mid Level
Responsibilities
- Train, debug, evaluate, and improve computer vision and 3D perception models.
- Develop ADAS capabilities for detection, classification, and instance segmentation across lanes, objects, traffic signs, and traffic lights.
- Build scalable data-generation pipelines, including auto-labelling and pseudo-labelling systems.
- Develop offline tracking and 3D reconstruction pipelines to propagate labels and generate large labelled datasets.
- Work across online, latency- and compute-constrained in-car models and offline large-scale data systems.
- Own ML work end to end and prioritize improvements based on system performance gaps.
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, including 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, latency, compute, and deployment constraints.
- Passion for autonomy and willingness to learn even if every qualification is not met.
Benefits
- Hybrid working model combining office collaboration with remote work across Wayve hubs.
- Relocation support and visa sponsorship where applicable.
- Equity participation.
- Learning and development budgets for training, conferences, and growth.
- Health insurance, dental coverage, enhanced maternity and paternity leave, retirement or pension benefits where applicable.
- Access to therapists, wellbeing partnerships, team socials, core hours, and hands-on work in vehicle workshops and labs.
Categories
ML EngineeringRobotics
About Wayve
Wayve builds end-to-end autonomous driving software—the vehicle-agnostic Wayve AI Driver—that runs on onboard compute and native sensors, licensed to automakers and fleet operators. Its platform spans ADAS and higher autonomy (L2+/L3 to robotaxi) and is designed to generalize across vehicle types and geographies. Founded in 2017 and headquartered in London, it tests its models across Europe, North America, and Japan, with a U.S. base in Sunnyvale, CA.