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Open nowPosted 90 days ago

多模态vlm算法工程师

zcnma1sv5kma/index41 open roles

Where
Suzhou, Jiangsu, Chinese Mainland
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Your applicationOpen now多模态vlm算法工程师zcnma1sv5kma/index · Suzhou, Jiangsu, Chinese Mainland

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Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 90 days ago

The posting

岗位职责 1. 负责基于多模态视觉语言模型（VLM）的视频理解技术落地，针对机器人操作场景，研发时序动作自动切分、行为语义识别、场景内容理解等算法，实现标注环节的自动化预标注，持续提升产线标注效率 2. 负责视频 - 文本语义对齐技术研发，基于 VLM 实现视频内容的结构化文本描述生成、动作短语映射、指令标签匹配，构建高质量的视频 - 文本配对数据集，支撑下游多模态模型训练 3. 负责标注全链路的智能质检算法建设，基于 VLM 搭建自动化质检流水线，实现无效行为样本过滤、标注一致性校验、标注错误自动识别、内容脱敏校验，全维度管控标注数据质量 4. 负责主流开源 VLM / 视频大模型的选型、领域微调与工程适配，针对机器人 Ego 视角、精细手部操作等垂直场景做专项优化，提升模型在细分场景下的准确率与鲁棒性 5. 跟踪多模态大模型、视频理解、大模型辅助标注方向的前沿技术进展，快速完成技术选型、原型验证与产线落地，持续迭代标注与质检的自动化能力

任职要求 1. 本科及以上学历，计算机、自动化、电子工程等相关专业，2 年及以上多模态 / VLM 算法研发与落地经验 2. 扎实的深度学习与 Transformer 架构基础，熟练掌握 PyTorch 深度学习框架，具备独立复现、微调、改造多模态模型的工程能力 3. 熟悉主流 VLM 模型（如 LLaVA、Qwen-VL、MiniCPM-V、InternVL、Video-LLaMA 等），有完整的模型微调、指令调优、推理部署实操经验 4. 具备视频理解、时序动作分割、视频文本检索 / 描述相关项目经验，了解视频时序建模、多帧融合等核心技术方案 5. 逻辑清晰，动手能力强，能独立完成技术调研、方案设计与落地验证，具备良好的跨团队协作与技术文档输出能力 加分项 1. 有具身智能、机器人操作、第一视角（Ego）视频理解相关项目经验 2. 有标注产线建设、智能质检、大模型辅助标注相关落地经验 3. 熟悉视频生成模型、时序大模型，有长视频理解、细粒度动作分析相关研发经验 4. 有人体 / 手部动作分析、细粒度行为理解相关研发背景 5. 有顶会顶刊论文、知名开源项目贡献、大规模多模态数据处理经验

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