美团商业增值-引擎后台算法资深工程师
社招全职核心本地商业-业务研发平台地点:北京状态:招聘
任职要求
1、深入了解至少一种深度学习编程框架(TensorFlow/Pytorch/Caffe/CNTK/Mxnet其它),对Cuda编程有实战经验的优先; 2、深入了解过Spark、Flink、特征场景下KV存储,并对数据湖有深入了解的同学优先; 3、掌握一种以上的开发语言,包括但不限于Java、C++、Python等,对面向对象思想有深入理解; 4、熟悉LLM主流推理引擎,如FasterTransformer、vLLM、TRT-LLM、SGLang等;熟悉常见的推理优化方法,如量化、FlashAttention、Continuous Batching等; 5、具有扎实的数据结构和算法设计基础,熟悉操作系统、数据库、网络等计算级基础知识; 6、责任心强,积极主动,有良好的沟通能力和团队合作能力。 具备以下条件优先 1、具备大型搜索、广告、推荐系统开发经验者优先; 2、具备对算法模型有深入理解,并有开发经验者优先; 3、具备头部大厂在GPU层面或者对TensorRT、TVM有深度实践者优先。
工作职责
1、负责商业增值的算法工程相关工作,建设机器学习Pipeline,提升算法迭代效率,统一机器学习的开发和部署,以标准化过程生产高性能模型,持续交付; 2、负责在线推理的优化工作,建设CPU+GPU的异构架构,解决大规模模型推理等问题,并能跟随模型的迭代持续进行编译优化,提升优化的普适性以及对新硬件的覆盖能力; 3、负责特征平台的优化升级工作,提升数据生产效率,实现算法场景下数据价值加速流通和赋能提效,并优化在线特征读取性能,且能前瞻性的看到新技术,结合实际场景预判引入; 4、负责算法迭代日常需求沟通,支撑算法生命周期的全链路迭代,理解算法需求的同时可以通用化的进行抽象,提升平台能力面对相似场景的复用性。 5、负责LLM推理引擎优化,基于业界先进经验设计开发及优化LLM推理框架。 6、负责高性能算子开发和优化,针对Transformer等结构,通过指令级、内存访问优化等手段,提升算子性能,充分利用硬件能力。 7、负责跟随业界LLM新技术,并赋能到业务中。
包括英文材料
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
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.
CUDA+
https://developer.nvidia.com/blog/even-easier-introduction-cuda/
This post is a super simple introduction to CUDA, the popular parallel computing platform and programming model from NVIDIA.
https://www.youtube.com/watch?v=86FAWCzIe_4
Lean how to program with Nvidia CUDA and leverage GPUs for high-performance computing and deep learning.
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
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.
面向对象+
https://liaoxuefeng.com/books/java/oop/index.html
面向对象编程,英文是Object-Oriented Programming,简称OOP。
https://liaoxuefeng.com/books/python/oop/index.html
面向对象编程——Object Oriented Programming,简称OOP,是一种程序设计思想。
https://www.youtube.com/watch?v=SiBw7os-_zI
Learn the basics of object-oriented programming all in one video.
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
推理引擎+
https://www.youtube.com/watch?v=_dvk75LEJ34
https://www.youtube.com/watch?v=XtT5i0ZeHHE
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.
数据结构+
https://www.youtube.com/watch?v=8hly31xKli0
In this course you will learn about algorithms and data structures, two of the fundamental topics in computer science.
https://www.youtube.com/watch?v=B31LgI4Y4DQ
Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.
https://www.youtube.com/watch?v=CBYHwZcbD-s
Data Structures and Algorithms full course tutorial java
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/
推荐系统+
[英文] Recommender Systems
https://www.d2l.ai/chapter_recommender-systems/index.html
Recommender systems are widely employed in industry and are ubiquitous in our daily lives.
TensorRT+
https://docs.nvidia.com/deeplearning/tensorrt/latest/getting-started/quick-start-guide.html
This TensorRT Quick Start Guide is a starting point for developers who want to try out the TensorRT SDK; specifically, it demonstrates how to quickly construct an application to run inference on a TensorRT engine.
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