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Open nowPosted 85 days ago

推荐大模型算法工程师 - TikTok Shop

ByteDance19,258 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now推荐大模型算法工程师 - TikTok ShopByteDance · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

15.1% 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. 2.4%1 day
  2. 6.5%3 days
  3. 15.1%7 days
This job: posted 85 days ago

ByteDance median: 23 days open

The posting

团队介绍：TikTok Shop 是 TikTok 旗下的内容电商业务，致力于成为用户发现并获取优价好物的首选平台。面向直播电商、视频内容电商、货架电商等多元购物场景，国际电商持续为全球用户提供更个性化、更主动、更高效的消费体验，也为商家提供稳定、可靠、可持续增长的平台服务，推动“新奇好物畅销全球，美好生活触手可得”的使命落地。 目前，国际电商算法团队分布在中国、美国、新加坡等多个国家和地区，深度参与全球化业务建设。加入我们，你将有机会面向全球用户、商家和商品生态，与跨区域的产品、工程、运营和业务团队协作，持续提升商品供给质量、用户购物体验、平台交易效率与履约体验，共同探索内容电商与智能购物的新模式。 Data-国际电商团队是 TikTok Shop 的核心算法技术力量，专注于电商场景下的算法创新与规模化落地，方向包括但不限于：生成式推荐与大规模 Foundation Model、多模态商品理解与内容生成、搜索与导购、智能客服、风控治理、物流履约优化、商家经营智能化，以及 Agentic 智能体在电商全链路中的应用。我们希望通过先进的算法能力，帮助用户更高效地发现感兴趣的商品，帮助商家实现更高质量的经营增长，并持续提升交易各环节的智能化水平。 在这里，你将与一流的产品和技术团队合作，面对复杂且真实的国际化电商挑战，推动前沿技术在大规模业务场景中落地，与团队一起创造更多可能。

1、参与推荐算法的探索——服务数亿真实用户、构建和重写算力时代下新的工业级推荐系统： 2、参与电商十亿级用户与商品的个性化推荐算法优化，覆盖视频、直播、货架场景下的召回、粗排、精排、混排全链路，每次迭代都会在线上直接创造真实业务价值； 3、LRM/LLM×工业推荐的正面碰撞，重塑下一代推荐范式： 1）Scaling up to Billion：把排序模型从亿级推到十亿级参数，联合训练与推理侧优化，探索推荐领域的scaling law——包括超长行为序列建模（KV Cache、序列压缩，UG分离，投机解码、动态batching等）、预训练、多场景多任务多阶段联合训练，针对推荐的特点进行模型结构设计和优化，提升MFU，探索在真实时毫秒级推荐系统下的scaling up的边界； 2）生成式推荐：基于语义ID（RQ-VAE/SID）与MLLM的一阶段生成式检索，用“beam search”与“test-time scaling”替代传统“多路召回+精排”漏斗，摆脱系统对ID记忆的路径依赖； 3）世界知识注入：用大模型的真实世界认知挖掘用户潜在兴趣与语义表征，突破纯ID共现的表达上限；探索用推理模型（LLM）对用户长周期意图做显式链式推断，提升推荐系统的发现性与新颖性； 4、极致的训推性能优化深入PyTorch底层算子（自研CUDA/Triton融合算子）、显存与计算图优化、分布式训练与推理加速，混合精度与低比特量化，把推荐场景特有的稀疏Embedding、变长序列、多任务Head打到硬件极限； 5、用Agent重写研发范式我们正在把Coding Agent深度嵌入算法研发流程：自动化特征挖掘与Pipeline生成、实验配置与训练任务的自动编排、模型评估与线上诊断的自动归因、负面案例的自动挖掘和巡检；你既是这套系统的使用者，也是它的建设者。

1、2027届获得本科及以上学历，人工智能、计算机、数学、统计等相关专业优先； 2、扎实的机器学习基础与工程能力：理解模型背后的数学，也写得出干净、高效、可复现的代码，熟练掌握主流算法与数据结构； 3、在机器学习、NLP、CV、推荐中至少一个方向有深入的研究或工程实践，并能清楚讲出你为什么这么做、以及可优化的方向； 4、对LLM/LRM技术有真实的热情，愿意把前沿方法推进到线上生效，而不止步于离线指标； 5、强烈的问题定义与拆解能力，面对模糊、无标准答案的业务问题时能自己找到突破口。

加分项： 1、在KDD、SIGIR、RecSys、WWW、ACL、NeurIPS、ICML、ICLR等顶会/顶刊发表过论文，或有高质量开源工作； 2、有CUDA/Triton算子开发、深度学习框架源码级优化、大规模分布式训练或高性能推理部署经验； 3、有LLM后训练（SFT/RLHF/DPO/GRPO）、Agent系统构建、或推理加速方向的实践经验； 4、主导或深度参与过搜索、广告、推荐、大模型方向的关键项目，有完整的从问题到线上收益的闭环经验； 5、ACM-ICPC、NOI、Kaggle等竞赛获奖经历。

为什么选择我们： 真实的十亿级流量、海量的算力预算、从算子到系统到业务的完整链路、开放的团队氛围，在这里你有机会和最优秀的算法工程师一起，重塑算力时代下的推荐系统，探索推荐的scaling law，能把自己的创造力和想法，变成真实影响上亿用户、百万商家达人的线上服务。

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