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Open nowPosted 67 days ago

【2027届校招】VLA大模型算法工程师

utopilot/campus9 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【2027届校招】VLA大模型算法工程师utopilot/campus · Shanghai, Chinese Mainland

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The clock on this job

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

Share of postings closed within
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  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 67 days ago

The posting

1. VLA模型研发与创新： 研究、设计、实现和优化应用于自动驾驶的VLA模型架构，探索视觉、语言（指令、场景描述、交通规则）与规划轨迹之间的对齐与映射机制。 开发基于大规模多模态数据的模型训练、微调与加速技术。 探索VLA模型在自动驾驶核心任务中的应用，如：场景理解与描述、驾驶指令理解与执行、复杂交互意图预测、端到端规划决策、可解释性驾驶行为生成等。 2. 算法开发与实现： 将前沿的VLA研究成果转化为可应用于实际自动驾驶系统的算法模块。 开发高效的数据处理、特征提取、模型训练与推理流程。 针对车载计算平台进行模型优化（如剪枝、量化、蒸馏），满足实时性要求。 3. 数据集构建与管理： 设计并推动构建高质量、大规模的自动驾驶多模态数据集（视觉+语言标注+动作序列）。 参与数据采集、清洗、标注策略制定与质量评估。 4. 系统集成与验证： 将VLA算法模块集成到自动驾驶软件栈中。 设计离线与在线评估指标，在仿真和实车平台上进行算法性能的全面测试、分析与迭代优化。 5. 前沿追踪与分享： 持续跟踪计算机视觉、自然语言处理、多模态学习、强化学习及自动驾驶领域的最新进展，特别是VLA相关的研究。 在团队内部分享知识和技术洞察，推动团队整体技术水平提升。

1. 教育背景： 计算机科学、人工智能、机器人学、电子工程等相关领域的硕士及以上学历。 2. 技术能力： 深度学习基础扎实：精通深度学习理论基础和开发框架。 多模态学习经验：深入理解并具备视觉-语言模型（如CLIP, BLIP, Flamingo, LLaVA, Qwen等）或VLA相关模型的研发经验。熟悉多模态表示学习、对齐、融合等技术。 编程能力：精通Python编程，具备优秀的软件工程能力和良好的代码习惯，熟悉Linux开发环境。 数据处理能力：熟练处理大规模数据集，熟悉相关工具和流程。 3. 经验要求： 3年及以上相关领的算法研发经验。有实际VLA项目经验者优先。 4. 个人素质： 出色的分析和解决复杂问题的能力。 强烈的自驱力、创新意识和探索精神，对前沿AI技术充满热情。 优秀的沟通能力和团队协作精神。 加分项 1. 有端到端，VLA自动驾驶、基于学习的决策规划模型研发经验。 2. 在顶级会议（CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, IROS等）发表过多模态学习、VLA、自动驾驶相关论文。 3. 具备大模型（LLM, VLM）训练、调优、部署经验，熟悉相关工具链（Hugging Face, DeepSpeed, Megatron-LM等）。 4. 有车载嵌入式平台（如NVIDIA DRIVE Orin/Thor）算法部署优化经验。

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