顺丰自然语言处理工程师(leader岗)
社招全职5-10年地点:深圳状态:招聘
任职要求
岗位要求: 1. 硕士及以上学历,博士学历优先,计算机/人工智能/数学/统计学等相关专业优先,具备 5 年以上团队管理经验(3 年+大语言模型方向工作经验); 2. 深入掌握大语言模型架构(如Transformer、LLaMA、Qwen、DeepSeek、GPT等),具备百亿参数规模以上的大语言模型Pre-train、Fine-tune、RLHF(GRPO, DAPO等)等完整研发及落地实战经验; 3. 精通Python,掌握至少一类深度学习框架(如PyTorch),熟悉多种分布式训练/推理加速技术(如DeepSpeed、Megatron、vLLM、FlashAttention等); 4. 具备大语言模型应用、Agent产品化经验,深刻理解自主决策的Agent建设方法论,曾主导或深度参与复杂业务场景的大语言模型部署与落地,有可量化的业务成果; 5. 熟悉大模型的部署、AI工程化,熟悉大模型的训练加速、推理加速、并发提升、资源节降技术,具备良好的系统工程能力; 6. 具备跨领域算法设计能力,可针对物流、客服、办公等复杂场景制定定制化AI方案,具备业务抽象与复合建模能力;
工作职责
岗位职责: 1. 负责制定大语言模型方向的技术战略与演进路线,持续引领团队在算法创新、系统部署、智能体架构等关键方向取得突破; 2. 全面统筹垂域大语言模型的研发、评估与部署生命周期,推动算法与系统能力的标准化、模块化和可复用建设; 3. 牵头在客服、销售、收派、运营、办公智能等核心领域构建智能体系统,重构关键业务流程,推动大语言模型的深度融合与落地应用; 4. 主导复杂业务问题的抽象建模,构建行业级、多任务、多场景的评估体系,覆盖模型精度、稳定性、安全合规等维度; 5. 制定并实施大语言模型系统性能优化策略,构建资源利用率高、弹性强的推理服务架构,提升模型部署效率与稳定性; 6. 引导团队围绕业务目标开展系统性大语言模型算法调研与分析,识别潜在问题与机会点,提出可落地的优化方案; 7. 紧跟大语言模型领域技术发展,持续输出行业趋势洞察,制定面向未来的技术路线与实施规划; 8. 管理算法团队,对团队成员进行技术引领、指导、职业发展辅导,保持团队先进性。
包括英文材料
学历+
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
Llama+
https://github.com/LlamaFamily/Llama-Chinese
Llama中文社区,实时汇总最新Llama学习资料,构建最好的中文Llama大模型开源生态,完全开源可商用。
https://www.llama.com/docs/overview/
This guide provides information and resources to help you set up Llama including how to access the model, hosting, how-to and integration guides.
GPT+
https://www.youtube.com/watch?v=kCc8FmEb1nY
We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具,在灵活性、可读性和性能上都具备相当的优势,近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
vLLM+
https://www.newline.co/@zaoyang/ultimate-guide-to-vllm--aad8b65d
vLLM is a framework designed to make large language models faster, more efficient, and better suited for production environments.
https://www.youtube.com/watch?v=Ju2FrqIrdx0
vLLM is a cutting-edge serving engine designed for large language models (LLMs), offering unparalleled performance and efficiency for AI-driven applications.
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
RLHF+
[英文] What is RLHF?
https://aws.amazon.com/what-is/reinforcement-learning-from-human-feedback/
Reinforcement learning from human feedback (RLHF) is a machine learning (ML) technique that uses human feedback to optimize ML models to self-learn more efficiently.
https://www.ibm.com/think/topics/rlhf
Reinforcement learning from human feedback (RLHF) is a machine learning technique in which a “reward model” is trained with direct human feedback, then used to optimize the performance of an artificial intelligence agent through reinforcement learning.
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