小鹏汽车Research Intern (Multimodal)

我们致力于构建下一代 空间智能（Spatial Intelligence）系统，让AI不仅能“看懂世界”，更能理解空间结构、推理物体关系、规划行动轨迹，并在虚拟或真实环境中持续学习与演化。 你将与团队一起： 研发具备空间理解、物体感知、轨迹预测与交互规划能力的智能体模型； 构建融合 视觉语言模型（VLM）与世界模型（World Model） 的系统，实现3D场景、深度、物理与可供性（Affordance）的联合建模； 使用 Game Engine（Unreal / Unity / Isaac Sim） 搭建高保真虚拟环境，用于数据生成与智能体评测； 基于 vLLM / Ray 构建高效多模态数据管线，实现大规模生成、自动标注与验证； 推动空间智能在机器人与具身智能领域的应用落地。

The computer vision algorithm intern will work in a dynamic team as part of the Video Engineering org which develops multi-modality based video quality assessment technologies in Apple Platform. We balance research and product to deliver the highest quality, state-of-the-art experiences, innovating through the full stack, and partnering with cross-functional teams to influence what brings our vision to life and into customers hands. Keywords: Multi-Modal LLM; Video Quality Assessment; Post-training

The computer vision algorithm intern will work in a dynamic team as part of the Video Engineering org which develops on-device computer vision and machine perception technologies across Apple’s products. We balance research and product to deliver the highest quality, state-of-the-art experiences, innovating through the full stack, and partnering with cross-functional teams to influence what brings our vision to life and into customers hands. Keywords: Agentic AI; Multi-Modal LLM; Video Foundation Model; Video Generative Editing

Location & Duration Sydney Central; 6-12 months Role Overview You will participate in the research and development of human aesthetic enhancement and spatiotemporally consistent editing technologies at Meitu. You will work directly with real, product-scale datasets and state-of-the-art algorithms. Depending on the internship track, your work may include (but is not limited to): ·      Fine-grained and controllable image / video aesthetic enhancement ·      2D / 3D human tracking and 3D reconstruction ·      Regression, reconstruction, and structural constraints of digital human models (e.g., SMPL) This role offers the opportunity to produce both production-ready technical outcomes and high-quality academic research results. It is a research-and-engineering-oriented internship, ideal for candidates with strong interest and capability in 3D vision fundamentals, human visual quality enhancement, video generation models, and 3D human modelling. Key Responsibilities ·      Research and implement algorithms related to depth estimation, multi-view generation, and 2D / 3D tracking with spatiotemporal reconstruction ·      Follow state-of-the-art 3D vision papers and open-source projects; reproduce experiments and adapt methods to practical applications ·      Collaborate with data teams to refine the 3D aesthetic development pipeline, improve data collection and quality evaluation, and establish foundations for high-quality scaling ·      Explore the integration of human structure priors (Skeleton / SMPL / Mesh) with multi-modal cues such as depth, normals, and optical flow in reconstruction and generative models ·      Assist in building data processing, evaluation, and visualization tools (e.g., immersive video aesthetic editing) to support rapid iteration ·      Enable high-quality projection of 3D features into 2D visual outputs, with the goal of producing A-level or above academic publications