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Open nowPosted 104 days ago

Super Sparks-校招-AI安全工程师

nio/campus869 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen nowSuper Sparks-校招-AI安全工程师nio/campus · 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. nio/campus 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 104 days ago

nio/campus median: 1 days open

The posting

写给AI安全技术破局者的话：这份JD是为了找到真正渴望在AI安全荒原上留下脚印的同路人。如果你看到这些描述感到兴奋而非畏惧，如果你在过去的学习/竞赛/研究中曾因“想得太大、做得太深”而被误解——那么，我们找的就是你。 不要被“顶会论文”、“CVE编号”等关键词劝退，只要你拥有远超同龄人的系统性技术深度和狂热的创新自驱力，请即刻投递。我们需要你的偏执与天才，来一起定义安全的下一个十年。

一、我们为何需要Super Sparks 当前，AI安全是全球技术竞争的前沿壁垒和挑战，我们对优秀的人才求贤若渴。蔚来数字安全部门不满足于仅仅跟随行业标准，我们的目标是定义下一代智能化安全的行业基准。 SuperSparks瞄准为优秀、拔尖（Top-tier）的应届毕业生设立。我们寻找能以黑客精神（hackthon）和思维重构系统、以批判者视角深究现象后面的原理、以架构师眼界设计未来的技术多面手。在这里，你面对的将是前沿理论中的未知威胁，你的成果将直接嵌入公司核心产品和技术底座，影响数百万的用户。

二、迎接“硬核”挑战 你将以前沿技术尖兵的身份，主导或深度参与以下颠覆性课题中的多个方向： 1、下一代AI安全架构的“从0到1”定义 不局限于现成的安全产品，而是主导下一代智能化安全防御体系的技术选型与架构设计。 深度攻克 AI安全基座（AI Safety Foundation）、AI安全数据底座开发及DevSecOps自动化闭环等高并发、高可用场景下的架构级难题。 针对具身智能、智能辅助驾驶等Physical AI系统，进行新型威胁和攻击面的安全评估，参与Physical AI系统的威胁建模与安全框架设计。 主导的模型、算法与设计方案，将定义团队未来3-5年的技术演进路线。

2、前沿未知威胁的“预言”式攻防 针对LLM、Agent、RAG等AI应用，开展极限红队测试，不仅挖掘已知风险，更要前瞻性预判因模型能力跃升带来的新型攻击面。 针对智能辅助驾驶感知/决策算法、VLA/VLM/NWM多模态模型、智能座舱交互系统等整车智能功能，开展AI安全评估与测试； 建立业界领先的对抗性攻击与防御知识图谱，将每一次攻防实战沉淀为具备自我进化能力的威胁情报基因库。

3、AI超级智能体与前沿模型研发 主导设计并训练安全垂直领域大模型，解决传统规则引擎无法覆盖的长尾风险。 参与整车AI Safety功能安全（预期功能安全SOTIF）与数字安全融合设计，构建覆盖“云-车-路”的全链路安全防御体系。 从零构建具备复杂推理、自主规划与多工具链调用的高可用AI Agent生态，以“AI原生”的颠覆性思维，彻底重构漏洞研判、应急响应等传统安全业务流。

4、高难度技术攻坚与产学研快速落地验证 敏锐捕捉全球顶会（S&P、CCS、NeurIPS、ICML）的最前沿动态，将大模型攻防、隐私计算、同态加密、数据投毒检测等尖端理论，可在较短时间内完成从“论文复现”到“工业级落地”的探索验证。 打破算法、工程与业务的部门墙，建立基于数据驱动的安全效能度量体系，超越、取代安全事件处置中的经验主义。

1. 学术背景：2027届海内外优秀博士毕业生，计算机科学、人工智能、网络空间安全、数学或相关交叉学科背景，具有扎实的数理基础与计算机底层理论功底； 2. 前沿AI研究能力：在机器学习（ML）、深度学习（DL）及大语言模型（LLM）领域有深厚的理论积累与丰富的实战经验。深入理解Transformer架构、RLHF/RLVR、Agent框架或多模态大模型等前沿技术，具备独立主导模型预训练、微调及推理优化的能力； 3. 深厚的安全攻防底蕴：对网络安全、系统底层原理及密码学有深刻理解，精通常见网络攻击与防御机制。能够将AI技术与安全业务深度结合，具备“AI for Security”或“Security for AI”的交叉研究视野； 4. 极致的工程落地能力：具备卓越的代码能力（精通Python/C++等），熟练掌握主流深度学习框架（PyTorch/TensorFlow等）。有将前沿算法从“学术Demo”转化为“工业级生产系统”的完整实践经验； 5. 技术领导力与极客精神：为人真诚、极具责任感与自驱力。对技术有极致追求，具备敏锐的行业洞察力、严密的逻辑思维以及解决复杂未知问题的破局能力；拥有出色的跨团队沟通与协作能力，能作为技术核心推动项目高效落地。

【加分项】 1. 在AI安全、大模型、系统安全或网络安全领域的国际顶级学术会议/期刊（如四大安全顶会、NeurIPS、ICLR、ACL等）发表过高质量论文； 2. 拥有高星开源项目贡献经历，或在知名国际安全/AI竞赛中取得过顶尖名次； 3. 有主导过大规模安全自动化平台、DevSecOps体系建设、或企业级AI Agent工作流架构设计的实战经验。

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