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Open nowPosted 129 days ago

优才-多模态交互算法工程师-X-Lab

agirobot/94699358 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now优才-多模态交互算法工程师-X-Labagirobot/946993 · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% 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. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 129 days ago

The posting

1. 训练流水线建设： 搭建与维护多模态模型训练 Pipeline（涵盖数据预处理、实验追踪、Checkpoint 管理与回归评测），支持音视频、状态序列等多模态输入。 2. Teacher-Student 蒸馏： 使用大模型/专家模块生成 Richer Labels，设计蒸馏目标、Loss 函数与 Hard-negative 机制，将高价值能力稳定转移至端侧，摆脱对云端的在线依赖。 3. 模型压缩与部署优化： 负责 PTQ/QAT、量化感知训练、剪枝与 KV/Cache 优化；导出 ONNX/TensorRT 等格式；在真实设备上死磕 Latency、显存、功耗与推理抖动。 4. 质量与回归治理： 建立可复现机制，系统性归因模型失效（数据、标签、结构或部署问题）；联合团队建设 Hard slices 与回放评测。 5. 运行时协同： 与系统侧拆分快慢路径，trade-off 端侧性能与业务收益，推动模型从“实验室能跑”跨越到“设备稳跑”。 6. 同时需要兼顾交互语义建模与任务定义（如回应对象判断、交互时机、主动策略等）

1. 硕士及以上在读，计算机、人工智能、自动化、电子信息等相关专业优先。 2. 熟练掌握 Python，熟悉 PyTorch 或其他深度学习框架。 3. 理解深度学习基础（Transformer、Attention、常见 loss 与优化方法）。 4. 有以下任一经验优先： LLM / 多模态模型训练（SFT / RLHF / LoRA） 语音 / 视觉 / VLM 项目经验 数据构造或训练 pipeline 搭建 5. 有多模态（音频+视觉）项目经验加分 6. 有 teacher-student 蒸馏或模型压缩经验加分 7. 熟悉交互类任务（如对话、agent、语音交互）加分 8. 做过模型对比实验、误差分析或 benchmark 评测加分

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