视频生成算法工程师 (Reward Model) 北京、深圳、上海 全职 研发 - 算法 职位描述 负责视频生成 reward model、benchmark 和评测、迭代体系建设，把主观视频质量拆解成可训练、可评测、可追踪的多维信号：1. 与数据团队合作，制定和把控视频生成打分标准。2. 对音视频理解专家模型进行质量评估、bad case 收集和持续迭代，如ASR、说话人、音色、语种、音效、音画同步等音频专家模型，以及OCR、目标检测、动作识别、切镜点检测、镜头运动估计等视觉专家模型。3. 训练多维 reward model，包括视觉 RM、音视频 RM、语义遵循 RM、美学 RM、崩坏判定模型等。4. 建立 benchmark 和自动评测 pipeline，结合人工评测、专家模型交叉验证 RM 准确度。5. 发现 benchmark 被 hack、RM 偏置和评测失真问题，持续优化评测可信度。6. 为后训练、数据清洗、模型选型和交付版本提供依据，并结合评测反馈、用户数据，持续迭代 RM。 职位要求 1.
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential
【Bambu Fellow Program】3D Foundation Model Campus 北京、深圳、上海 实习 研发 - 算法 日常实习 职位描述 About Bambu Fellow Program：We are seeking the world’s most brilliant young researchers. Here, you will do more than just train models—you will leverage foundation models to
Department：Avatar 职位：制造大模型算法工程师（Downstream） 职责描述： 与资深制造大模型算法工程师合作，开发基于多模态电池基础大模型的下游应用。 参与开发和优化多个具体应用模型，包括电芯质量评估模型、生产过程优化模型、电芯设计优化模型、电芯性能预测模型以及电芯设计生成式模型。 协助实施和优化数据处理管道，确保数据准确性和一致性，以支持下游应用开发。 应用机器学习和深度学习技术进行模型训练、验证和优化。 分析和处理复杂的数据集，提取关键特征以改进模型性能和应用效果。 协助跨职能团队理解业务需求并制定相应的技术实现方案。 持续跟踪最新技术发展，协助引入前沿方法提升模型应用效果。 任职资格： 计算机科学、电子工程、统计学或相关领域的硕士学位。 至少3年以上在机器学习或AI领域的实际工作经验，有制造业或电池生产相关经验者优先。 熟悉机器学习和深度学习算法，具备多模态数据处理与应用开发经验者优先。 熟练掌握Python、TensorFlow、PyTorch等常用的机器学习框架和工具。 具备处理表格数据、时序数据和图像数据的能力，并能够将这些数据应用于具体的模型开发。 良好的沟通能力和团队协作精神，能有效与跨职能团队合作。 具备良好的问题解决能力和学习新技术的意愿。 Responsibilities: Cooperate with senior AI/ML engineers to develop downstream applications based on multi-mode battery basic large model. Participate in
Who You Are You are a talented, hands-on researcher who thrives in a fast-paced environment, is self-directed, a team player, and knows how to get things done efficiently. You have deep understanding of the transformer architecture,
空间智能算法资深工程师（机器人 World Model 方向） 急招 广州、上海、深圳 全职 通用智能板块 职位描述 职位描述负责机器人与具身智能场景的空间智能及 World Model 算法研发，围绕三维重建、空间理解、时空状态表征、未来预测与生成式数据方向，建设数据构建、模型训练、算法评估与优化的完整能力闭环，提升机器人对环境状态、动态变化及动作结果的建模与预测能力，为感知、规划、决策及策略学习等核心业务场景提供算法支持。岗位职责1、参与 World Model 与空间智能算法研发及模型训练负责三维场景重建、空间理解、时空表征、视频/生成式数据及 World Model 等方向的算法研发与迭代，探索基于视觉、深度、点云、机器人状态及动作信息的统一环境建模，提升模型几何精度、时空一致性、未来预测能力与跨场景泛化能力；2、参与机器人环境状态与未来预测能力建设围绕机器人与环境交互过程，研究场景状态编码、动态目标建模、动作条件预测及未来状态生成等技术，探索 latent state / world representation 等统一表征方式，支持机器人对未来环境变化及动作执行结果进行预测，为规划、决策和策略学习提供模型能力；3、参与数据质量评估体系建设建立重建、预测及生成数据的质量评估标准、指标体系与问题归因机制，重点评估几何一致性、时序一致性、动态合理性、动作响应一致性及生成质量，支撑 World Model 训练与算法优化闭环；4、参与数据生产流程优化构建或优化面向机器人感知、规划、场景理解及 World Model 训练的数据生产流程，打通真实数据、仿真数据与生成式数据，提升数据覆盖度、多样性及时序完整性，补全复杂交互、稀有状态及长尾场景；5、参与生成式数据与仿真能力探索及落地探索图像/视频/3D生成、未来状态生成、仿真合成等方式构建机器人训练与评测数据，研究基于条件控制、轨迹约束及动作输入的数据生成方法，提升生成数据的真实感、可控性与物理一致性，推动在 World Model、策略训练与算法评测中的实际应用；6、参与技术方案设计与跨团队协作与感知、规划、控制、强化学习、数据、工程及产品团队协作，推动 World Model 技术方案设计、数据标准制定、模型接口定义及算法能力的系统化落地，探索 World Model 在机器人预测、规划、决策和策略优化中的应用。 职位要求 1、本科及以上学历，计算机、AI、自动化、机器人、测绘遥感等相关专业；2、在三维重建、空间理解、World Model、视频生成、生成式数据、机器人或具身智能方向中至少一个方向有完整项目经验；3、具备较强的算法问题拆解与系统性分析能力，能够围绕环境建模、时序预测、生成质量或机器人任务需求提出可落地的优化方案；4、具备较强的工程化能力，可独立完成数据处理、模型训练、评估与实验 pipeline 开发，并能够支持大规模时序数据及多模态机器人数据的训练与分析；5、具备较强的论文阅读与方法复现能力，熟悉或持续关注 World Model、视频生成、3D Foundation
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