Jobs at WeRide.ai

Join WeRide as a Software Engineer to tackle complex AI and robotics challenges in autonomous driving technology, focusing on computer vision, sensor fusion, and machine learning.

Develop scalable PaaS and IaaS platforms for autonomous driving, improving performance and efficiency through architecture and data processing.

WeRide is seeking a Backend/Infrastructure Software Engineer with 3+ years of experience to build large-scale systems for autonomous driving technologies.

Develop and integrate motion planning algorithms and software for autonomous vehicles, ensuring computational efficiency and real-time performance in various conditions.

Assist in HR operations by supporting recruitment processes, managing documents, coordinating activities, and handling confidential information. Must work onsite.

The Production Engineer will debug software and hardware for autonomous vehicles, analyze performance, and develop improvements for incident management.

Develop and deploy perception and deep learning models (CV, VLMs/LLMs), behavior prediction, localization, motion planning, control, and high-fidelity simulation for autonomous driving.

Design, implement and lead comprehensive testing plans for L4 autonomous vehicles; perform functional, performance, and safety testing; analyze test data, identify and fix issues; oversee Singapore testing operations and collaborate with partners; travel internationally for local deployments.

Join the AI team to develop and deploy real-time perception and deep learning models for autonomous vehicles. Build and optimize data pipelines, research object detection, segmentation, road understanding, motion prediction, and apply multi-modal sensor fusion for robust onboard perception.

Oversee project deployment and operations of autonomous vehicles in Singapore, ensuring communication with stakeholders and facilitating vehicle safety tests.

Label, annotate, and QA text/image/audio/video datasets per guidelines. Perform random and targeted checks, identify and escalate edge cases, track quality metrics, and provide feedback to annotators to meet productivity and accuracy targets.

Entry-level software engineer for autonomous vehicle systems. Build real-time in-vehicle systems, data transport and logging, communication between embedded devices and hosts, cloud/backend ML infrastructure, model deployment and evaluation, GPU/CPU kernel optimization, and tooling to support developers and large-scale model workflows.

Develop efficient ML solutions for perception including sensor fusion, obstacle detection, scene understanding, and robust onboard systems.

Label and review large text, audio, image, and video datasets to ensure annotation quality and consistency; follow project guidelines, meet targets, and provide process feedback to ML teams.