快手【快Star-X实习】引擎研发工程师
实习兼职J1020地点：北京状态：招聘
任职要求
1、硕士及以上学历，专业不限，计算机相关专业优先； 2、掌握Python/C++编程语言，熟练使用Pytorch 框架或者有 vllm/tensorrt 等推理框架使用经验； 3、具备分布式训练或HPC基础知识，了解集合通信和CUDA编程或者 arm/x86 SIMD 指令更佳； 4、有机器学习平台开发和深度学习框架开发等领域开发经验； 5、有模型训练推理调优相关工作经历，包括搜广推模型或CV/NLP模型，熟悉Transformer/Bert/GPT等模型结构更佳。
工作职责
1、参与快手模型训练推理的深度研发，提升模型训练、推理的框架性能； 2、与算法部门合作，为快手大模型定制训练方案，探索大模型的 RLHF、MoE、多模态、longcontext等前沿方向，提升训练性能； 3、分析服务器、手机端模型的推理特点，对计算、访存和通讯做出针对性优化； 4、关注前沿技术，跟进业内最新研究进展和应用趋势，提出创新思路和方向。
包括英文材料
学历+
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.
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
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.
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.
HPC+
https://www.ibm.com/think/topics/hpc
HPC is a technology that uses clusters of powerful processors that work in parallel to process massive, multidimensional data sets and solve complex problems at extremely high speeds.
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.
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
NLP+
https://www.youtube.com/watch?v=fNxaJsNG3-s&list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S
Welcome to Zero to Hero for Natural Language Processing using TensorFlow!
https://www.youtube.com/watch?v=R-AG4-qZs1A&list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Natural Language Processing tutorial for beginners series in Python.
https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4
The foundations of the effective modern methods for deep learning applied to NLP.
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.
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.
相关职位
实习J1020
1、参与快手大规模深度学习推理引擎、大模型训练解决方案的研发与优化，包括大模型推理、模型训练框架、微调平台等； 2、参与底层算子的优化、通过优化访存pattern、计算提升推理性能。与算法部门合作，为公司大模型定制训练方案，探索RLHF、MoE、多模态、longcontext等前沿方向，提升训练性能； 3、优化推理框架上层调度策略，通过机内、机间的计算任务调度和通讯优化提升引擎性能；优化现有大语言模型相关工具和平台，提高模型训练、维护效率，降低成本，提升训练服务稳定性。
更新于 2025-06-04
校招J1001
1、参与快手大语言模型、多模态基座模型的训练/推理引擎研发及优化工作； 2、参与快手自研生成式推荐大模型训练全链路开发和优化，以及快手广告、电商、直播、搜索等全域模型的训练全链路研发与优化； 3、设计和优化分布式训练框架，通过混合并行，通信计算overlap、低精度训练等方法解决超长序列、超大规模moe场景下的训练效率问题； 4、参与通用高性能RL框架的开发和优化，包括但不限于高效rollout、高效RL链路调度优化等； 5、通过各种技术手段持续优化性能，降低推理成本，包括但不限于：算子/编译优化、异构推理、模型量化&蒸馏、分布式并行等。
更新于 2025-07-25
校招J1001
参与快手大模型推理引擎研发，工作内容包括： 1、参与大模型推理引擎的设计和研发，支撑快手自研以及开源模型的快速部署和高性能推理 2、通过各种技术手段持续优化性能，降低推理成本，包括但不限于：算子/编译优化、异构推理、模型量化&蒸馏、分布式并行等 3、支持RL中的多样化采样、generation性能优化等
更新于 2025-07-18
实习J1020
1、参与研发业界领先的深度学习编译技术，落地计算优化、显存优化及分布式优化技术到训练框架和推理框架中，赋能深度学习算法落地； 2、XLA 相关编译优化功能开发； 3、结合pytorch/tensorflow等上下游框架适配与集成； 4、异构大模型推理引擎优化，负责调研NV 上各种推理引擎的优化技术，并支持大模型推理各种优化技术在异构硬件上的落地。
更新于 2025-05-14