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Open nowPosted 159 days ago

资深VLM大模型算法工程师

nwd4iy9rd2s/referral79 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now资深VLM大模型算法工程师nwd4iy9rd2s/referral · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. nwd4iy9rd2s/referral postings stay open a median of 1 days.

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. 57.8%60 days
This job: posted 159 days ago

nwd4iy9rd2s/referral median: 1 days open

The posting

我们聚焦具身智能领域前沿技术研发，打造具备自主感知、决策、执行能力的通用智能体系统，现面向行业招募核心技术人才。本次招聘的资深 VLM 多模态大模型工程师，将作为团队技术核心，主导具身智能 Agent 系统核心视觉语言大模型的全链路优化与迭代，直接决定智能体对物理世界的感知理解能力、自主决策能力与任务落地效果，是具身智能系统研发的核心技术岗位。

【核心职责】 1、负责具身智能 Agent 系统核心 VLM 多模态大模型的架构优化、算法迭代与性能提升，针对物理场景感知、机器人交互、自主决策等垂直场景完成模型定制化适配与轻量化落地。 2、主导 VLM 模型在物理世界三维感知、场景语义理解、多模态信息融合、长程时序推理等核心能力的技术攻关，解决真实物理环境下的视觉遮挡、动态干扰、跨场景泛化等行业难题。 3、协同机器人控制、算法工程、产品落地团队，完成 VLM 模型与具身智能系统的深度耦合、端侧部署与工程化优化，保障模型在真实场景下的实时性、稳定性与鲁棒性。 4、跟踪具身智能、多模态大模型领域国际顶会（ICRA、IROS、RSS、CVPR、ICML 等）前沿技术，完成技术预研、方案验证与专利、论文沉淀，搭建团队核心技术壁垒。 5、负责模型训练、微调、评测体系的搭建与优化，制定多模态感知、具身决策能力的量化评测标准，持续迭代模型核心性能指标。

【任职要求】 1、计算机/AI 基础： 计算机科学或相关专业硕士及以上学历，具备极强的学术科研与Python/Pytorch工程实现能力，具备扎实的算法推导与问题排查能力。 2、精通视觉 - 语言多模态大模型的核心原理、架构设计与训练流程，熟练掌握 CLIP、BLIP、LLaVA、Qwen-VL 等主流多模态模型的源码解读、微调优化与二次开发。 3、时延优化经验：深刻理解 Transformer 推理瓶颈，有处理多模态大模型（VLM）首 Token 延迟（TTFT）优化的成功案例，具备vLLM / SGLang等推理加速框架的实战经验。 4、熟悉具身智能 Agent 系统基本架构，理解物理世界交互、时序任务规划、闭环决策的核心逻辑，能够基于 VLM 模型完成智能体感知与决策模块的方案设计。 5、具备良好的代码规范、工程化思维与问题解决能力，能够独立负责核心模块的研发与迭代，具备优秀的团队协作与沟通能力。 6、具备良好的英文文献阅读与技术拆解能力，能够快速跟踪、复现与落地前沿多模态与具身智能技术。 7、有高影响力AI企业核心技术研发经验，能够承受技术攻关节奏，具备极强的自驱力与技术创新力。

【加分项】 1、有顶会（CVPR/ICCV/ECCV/ICRA/IROS/RSS/ICML/NeurIPS）第一作者论文，或多模态、具身智能相关发明专利授权成果。 2、主导过落地级具身智能机器人、自主决策 Agent、家用 / 工业智能体产品的 VLM 核心模块研发与量产落地经验。 3、精通大模型轻量化、端侧推理优化、多模态模型与控制算法联合优化，有高实时性、低算力场景模型落地经验。 4、参与过开源多模态大模型、具身智能框架的研发与贡献，有知名开源项目维护经验。

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