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Open nowPosted 69 days ago

端到端环境认知推理算法工程师（数据驱动 / VLM 方向）

yesv-desaysv/index444 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now端到端环境认知推理算法工程师（数据驱动 / VLM 方向）yesv-desaysv/index · Shanghai, 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. yesv-desaysv/index 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 69 days ago

yesv-desaysv/index median: 1 days open

The posting

岗位职责 面向自动驾驶环境认知与导航决策场景，基于 VLM 多模态大模型开展算法研发与升级，通过多模态语义增强突破长尾场景泛化瓶颈，补齐决策可解释能力，支撑算法量产落地与场景扩域。 负责 VLM 领域微调、知识蒸馏、特征对齐的全链路开发，推进从标签注入浅度融合到特征层深度融合的技术迭代，搭建统一的多模态环境认知决策模型架构。 负责多模态数据集建设、算法评测体系搭建与数据闭环落地，基于路测失效案例开展根因分析，驱动算法持续迭代优化。 配合工程团队完成模型车载轻量化、推理优化与部署适配，跟踪 VLM/VLA、多模态世界模型等前沿技术，开展技术预研与方案验证。

任职要求 本科及以上学历，计算机、人工智能、自动化、车辆工程等相关专业；深度学习理论基础扎实，熟练使用 PyTorch 框架，精通 Python，熟悉 C++ 与 Linux 开发环境。 具备 VLM / 多模态大模型项目实战经验，熟悉主流开源 VLM 模型架构，掌握 LoRA/QLoRA 微调、多模态特征对齐等核心技术。 具备知识蒸馏、模型轻量化、数据驱动算法迭代的实践经验，能够独立完成从数据处理、模型设计到实验验证的全流程开发。 具备较强的问题分析与根因定位能力，自驱力强，拥有良好的跨团队沟通协作能力。

加分项 有自动驾驶环境认知、导航决策、场景理解相关项目经验； 有车载边缘端模型部署、量化压缩、推理优化相关经验； 熟悉高精地图 / SD 地图数据格式与导航拓扑逻辑； 有世界模型、VLA 相关技术预研或项目经验。

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