Senior Staff Digital World System Engineer

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R D in AI, machine learning, and smart connectivity.

Responsibilities

Be responsible for the overall architecture design and technological evolution of the next-generation synthetic data and Digital World generation system, supporting large-scale model training, simulation and evaluation in the directions of autonomous driving, robotics and embodied intelligence. Lead the construction of core capabilities in directions such as Digital City, Digital Twin, and World Model, and build a high-fidelity, highly scalable virtual world generation and closed-loop simulation system. Be responsible for the R D of algorithms and systems related to 3D/4D scene reconstruction, including multi-view 3D reconstruction, Gaussian Splatting, NeRF, SLAM/SfM, spatiotemporal scene modeling and other directions, to build large-scale spatial understanding and reconstruction capabilities.

Build a synthetic data production engine for perception, prediction, planning, VLA and robot model training, realizing high-quality, high-efficiency and low-cost data generation and delivery. Explore the application of cutting-edge technologies such as Generative AI, Diffusion, World Model and Physics Simulation in the field of simulation and data generation, and promote the evolution of data closed-loop towards automation and intelligence. Build a closed-loop simulation system for Digital City, realizing capabilities such as problem scenario reproduction, model playback verification, long-tail problem mining and automated evaluation.

Collaborate in depth with teams of autonomous driving algorithms, robotics, simulation platforms, data Infra and training platforms to promote the integration and large-scale application of synthetic data and real data systems.

Benefits

of model training. Be responsible for the construction of synthetic data platform and team, promote the platformization, engineering and large-scale landing of core technologies, and form long-term evolution capabilities.

Requirements

Master's degree or above in Computer Science, Artificial Intelligence, Robotics, Computer Vision, Computer Graphics or related majors. Have R D experience in related fields such as synthetic data, simulation systems, 3D vision, neural rendering or embodied intelligence. In-depth understanding of technologies related to 3D reconstruction and spatial modeling, including but not limited to SfM, SLAM, NeRF, Gaussian Splatting, Differentiable Rendering, Photogrammetry and other directions.

Candidates with relevant project experience in Digital Twin, Digital City, simulation platforms or large-scale virtual scene generation are preferred. Familiar with cutting-edge technology directions such as multi-modal large models, World Model, Generative AI, Diffusion and Reinforcement Learning, and have an in-depth understanding of data-driven model training systems. Have R D experience in large-scale distributed systems, data generation platforms or high-performance rendering systems, and be able to promote the engineering landing of complex systems.

Candidates familiar with Unreal Engine, Unity, Omniverse, physical simulation engines or graphics rendering pipelines are preferred. Have excellent system architecture capabilities and cross-team collaboration capabilities, and be able to promote complex technical projects from research to production landing.