Senior Research Scientist (Multimodal Large Language Model) - PICO

About the Team PICO-MR team is dedicated to pioneering core technologies for intelligent human-computer interaction in MR environments, with a focus on integrating multimodal large language models (MLLM) and tool-use capabilities to redefine user experiences. Our R&D directions cover cutting-edge fields including multimodal scene understanding, MLLM-based agent systems, tool-augmented MR interaction, 3D environment perception, and AIGC-driven content generation. Within MR scenarios, our work spans: MLLM optimization and adaptation for MR, intelligent task execution with tool use, multimodal scene understanding (vision, point clouds, text), AIGC-based scene generation, depth estimation (Mono/Stereo/MVS), 3D environment perception, large-scale 3D scene reconstruction (3DGS, NeRF, etc.), visual localization, and lighting estimation—encompassing both fundamental research breakthroughs and industrial-grade solution deployment. Responsibilities: 1. Lead the R&D of multimodal large language models (MLLM) tailored for MR scenarios, integrating vision, point clouds, text, and other multimodal information—including model architecture optimization, cross-modal alignment, data construction, evaluation system enhancement, and end-to-end training/inference acceleration. 2. Drive the research and implementation of MLLM tool-use capabilities in MR environments, enabling models to proficiently utilize spatial interaction and spatial computing-related professional tools, support tool calls for both single-turn and multi-turn conversations, and solve complex user tasks through interaction. 3. Address key challenges in long-horizon, multi-turn tool-augmented tasks in MR, such as context memory management, tool selection strategy, and error correction mechanisms. 4. Keep abreast of cutting-edge technologies in MLLM, multimodal intelligence, and tool-use research, and lead the application and deployment of innovative technologies in PICO's MR products. 5. Collaborate with cross-functional teams (including software engineering, product design, and hardware development) to translate research outcomes into practical features that enhance user experience.