蚂蚁金服蚂蚁数字科技-数科技术部-AI平台研发工程师
社招全职3年以上技术类-开发地点:北京 | 上海 | 杭州状态:招聘
任职要求
1. 3年以上工作经验,计算机、数学等相关专业本科以上学历; 2. 具备Java或者Python语言的开发能力,具备机器学习平台研发经验; 3. 熟悉Spark MLlib、Tensorflow、Pytorch、Caffe等引擎,具有相关引擎研发经验者优先; 4. 熟悉大模型训练框架Megatron-LM/Deepspeed,具有相关引擎研发经验者优先,有百亿/千亿大模型训练调优经验者优先; 5. 有自然语言/多模态大模型、深度序列模型、深度生成模型、图神经网络、知识图谱等相关技术或者落地经验者优先; 6. 在机器学习/CV/NLP/人工智能相关领域有顶会论文或者有算法竞赛top经验者优先; 7. 有科技类(平台类)商业化产品研发经验者优先。
工作职责
1. 负责商业化的机器学习平台研发;负责相关平台的能力建设、平台运维、质量保障; 2. 负责开发大模型应用和落地相关算法服务和平台,包括不限于大模型训练平台、大模型部署平台、Agent平台、大模型交互平台等; 3. 负责相关的技术预研和创新落地;技术创新如专利、论文的撰写; 4. 负责外部技术影响力交流等。
包括英文材料
学历+
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.
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.
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.
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.
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.
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
Megatron+
https://www.youtube.com/watch?v=hc0u4avAkuM
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.
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/
DeepSpeed+
https://www.youtube.com/watch?v=pDGI668pNg0
Caffe+
https://caffe.berkeleyvision.org/
Caffe is a deep learning framework made with expression, speed, and modularity in mind.
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