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Open nowPosted 252 days ago

大模型训练推理实习生-商业信任与安全

ByteDance19,258 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now大模型训练推理实习生-商业信任与安全ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.4% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 23 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.2%3 days
  3. 11.4%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 252 days ago

ByteDance median: 23 days open

The posting

ByteIntern：面向2027届毕业生（2026年9月-2027年8月期间毕业），为符合岗位要求的同学提供转正机会。 团队介绍：商业化信任与安全研发团队致力于构建业界领先的智能审核系统，通过前沿 AI 技术保障商业内容安全与合规，提升用户客户的信任。团队通过研发大模型基座、先进的审核大模型和审核系统，持续提升大模型系统对复杂商业化内容的理解、让准确理解遵循安全规则、基于规则深度推理并拉齐人与机器之间的认知，并能感知发现潜在问题，并用Agent高效处理审核问题、自动迭代审核系统，为商业内容安全提供全链路、智能化的技术支撑。

1、大模型训练框架研发与效率优化：负责多模态大模型（涵盖视频理解/视频生成/Omni的预训练、SFT、RL等任务）的训练效率优化，深入应用数据并行、模型并行、流水线并行及通信优化等分布式训练技术，持续提升训练吞吐与资源利用率； 2、高性能推理框架优化：面向商业信任与安全业务场景，设计并实现适配自研多模态理解/生成/Omni模型架构的高性能推理框架，针对广告审核等高并发、低延迟场景进行端到端性能调优； 3、模型推理加速技术研究：探索并落地前沿推理加速技术，包括模型量化、知识蒸馏、结构剪枝、稀疏Attention、低精度计算（FP8/INT4）、NPU定制算子开发、并行解码优化、投机采样及PD分离等，全面提升推理吞吐与能效比； 4、技术沉淀与输出：持续跟踪业界前沿，推动核心技术在业务场景中规模化落地；通过技术分享、专利撰写与高水平论文发表，构建团队技术影响力。

1、2027届硕士及以上学位在读，计算机、电子信息或相关专业优先； 2、扎实的机器技术基础，了解前沿的AI技术，有不错的工程实践经验优先； 3、有大模型训练优化经验，熟悉VeRL/FSDP/DeepSpeed/Megatron等分布式训练框架经验者优先； 4、熟悉模型推理加速的研究和技术进展，包括但不限于模型量化、剪枝、算子优化等； 5、了解业界常用的大语言模型推理加速框架，如SGLang，vLLM，TensorRT-LLM等； 6、熟悉LLM模型训练优化，了解混合精度训练、分布式训练等训练加速方法优先；训练/推理优化满足一条即可。

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