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Open nowPosted 41 hours ago

视觉算法实习生 - PICO

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now视觉算法实习生 - PICOByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 27 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 41 hours ago

ByteDance median: 27 days open

The posting

团队介绍：作为一家拥有自主创新和研发创造能力的科技品牌，PICO致力于成为领先的世界级XR平台，成就开发者与创作者，共同为全球消费者创造更美好的生活体验。我们开创性地将虚拟现实扩展到了多个领域，为运动、视频、娱乐等消费级场景带来了全新体验；并广泛应用在教育、医疗和企业培训等商用场景，给全球企业级用户提供了多元化的VR解决方案。

日常实习：面向全体在校生，为符合岗位要求的同学提供为期3个月及以上的项目实践机会。

1、参与XR设备人机交互相关基建建设，包含数据采集/3DGS多视图重建与高质量渲染/生成、Diffusion多视角图像/视频合成/可控生成，搭建高效可扩展的生成算法管线； 2、研究面向XR设备的人机交互多模态大模型，包括用户意图理解/上下文感知/视觉语言理解/多模态信息融合/连续交互建模等方向，提升模型在复杂真实环境中的感知与交互能力； 3、参与智能体主动式服务能力研发，探索基于用户状态/环境上下文与长期行为信息的主动感知/主动决策与主动服务机制，包括但不限于多模态Agent/长期记忆/上下文建模/任务规划与个性化交互； 4、研究面向长期使用场景的用户状态与健康识别相关算法，结合眼动追踪/人体姿态/情绪状态及行为模式等多模态信号，探索基于大模型的长期健康状态理解/趋势建模与异常识别能力； 5、参与多模态大模型训练/微调/评测与推理优化，包括数据构建/指令微调/偏好优化/多模态对齐/模型压缩及端侧/云端推理效率优化等工作。

1、硕士及以上学位在读； 2、具备优秀的编程能力，熟练掌握Python/C/C++等计算机语言，熟悉常见深度学习框架/多模态大模型（VLM）/大语言模型（LLM）/Agent架构相关的算法技术；扎实的CV/图形学基础，包括多视几何/相机模型与标定/重建与渲染/时序一致性/优化与数值计算，在AIGC/3D视觉领域具备扎实的算法基础，有AIGC相关项目经验； 3、熟悉LLM/VLM或Agent架构，熟悉RL算法，包括GRPO/PPO/DPO/判别式及生成式RM/Multi-Agent算法+工程技术，有多模态内容理解应用/AI Agent应用经验； 4、熟悉基于眼动信号的情绪识别/认知负荷检测算法，并有相关研究经验。

加分项 1、在CVPR/ICCV/ECCV/NeurIPS/ICLR/ICML/ACL/EMNLP/AAAI/ACM MM/CHI/UbiComp/ISMAR/IEEE等人工智能/计算机视觉/多模态/人机交互或XR领域高水平会议/期刊发表过论文，或具有扎实的相关科研项目经历； 2、具备视频生成文/图生视频/长视频/高清，场景生成全景/相机可控/世界模型，新视角合成3D/4D经验； 3、熟悉大模型训练、后训练与对齐技术栈，对SFT/DPO/PPO/GRPO/RLHF/Agent RL等方法有实践经验，熟悉VeRL/TRL/EasyR1等训练/强化学习框架，具备分布式训练/数据Pipeline/模型评测体系或训练基础设施建设经验者优先，在ACM-ICPC/Kaggle等高水平算法或数据竞赛中取得优异成绩者优先； 4、具有XR/AR/VR场景下的人机交互算法经验，包括但不限于Eye Tracking/Gaze Estimation/Hand Tracking/Body Pose Estimation/Gesture Recognition/Egocentric Perception/Spatial Computing/智能可穿戴设备感知等方向； 5、在多模态大模型/Multimodal Agent/强化学习/长期记忆/个性化智能体或主动式智能系统等方向有深入实践，主导或核心参与过具有较强技术影响力的开源项目/研究项目或产品级算法系统者优先。

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