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Open nowPosted 38 days ago

校招-大模型训练框架研发工程师(智能辅助驾驶方向)

nio/campus869 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now校招-大模型训练框架研发工程师(智能辅助驾驶方向)nio/campus · Shanghai, Chinese Mainland
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The clock on this job

Early applications get read.

12.1% 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. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 38 days ago

nio/campus median: 1 days open

The posting

负责大模型训练框架的开发、优化、跟踪大模型训练优化前沿技术,并将其应用于智能辅助驾驶大模型的训练; 负责自动智能辅助驾驶模型训练相关的资源及效率优化,深入分析大模型训练瓶颈,从数据处理、模型计算、多机通信、显存优化等多角度全链条开展优化; 负责探索并落地 AI Agent 在大模型训练优化中的应用,面向智能辅助驾驶场景构建自动化训练优化能力,包括超参数调优、训练过程监控、异常诊断、性能瓶颈分析与优化建议生成、代码生成合并、评测 Harness等; 负责模型训练稳定性工具建设,能在模型训练异常时,通过监控指标及时发现问题原因并解决; 从计算专业角度,赋能算法,影响算法设计硬件友好的模型结构。

2027届毕业硕士及以上学历,计算机、软件工程、人工智能等相关专业优先; 工程或机器学习算法有深厚的功底和经验; 由衷热爱技术,可以一线写代码,查问题; 历史上解决过难题,遇到难题时能静下心,没有畏难情绪,能查到底层,观察敏锐,逻辑清晰; 有强烈的工作责任心,较好的学习能力、沟通能力和自驱力; 良好的沟通协作能力,能和团队一起探索新技术,推进技术进步。 加分项: 熟悉LLM、NLP、CV、语音相关的算法和技术,熟悉大模型训练、Diffusion、RL算法者优先; 有以下某一方向领域的经验:CUDA,RDMA,AI Infrastructure,HW/SW Co-Design,High Performance Computing,ML Hardware Architecture (GPU、Accelerators、Networking),ML for System,Distributed Storage; 有顶会论文、开源贡献、或工程项目能展示你能力者优先。

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