阿里巴巴阿里国际站-AI+工程师-技术质量
社招全职4年以上技术类-开发地点：杭州状态：招聘
任职要求
1. 本科及以上学历，计算机、人工智能、数学、统计或相关专业；3年以上软件开发经验，具备大模型工程化落地、微调及应用开发的实际项目经验。 2. 工程基础：精通Python，熟悉Java/Go/C++至少一种；熟练掌握主流工程框架（如 Spring Boot、Django、React/Vue 等），具备高并发、分布式系统设计与开发能力；熟悉数据库（MySQL/PostgreSQL）、缓存（Redis）、消息队列（Kafka/RabbitMQ）等中间件的选型、优化与运维。 3. ML与数据基础：熟练使用 Python 进行数据处理，掌握 Pandas、NumPy、SQL 等常用工具；理解常见机器学习与深度学习算法原理；熟练使用至少一种主流深度学习框架（如：PyTorch），并具备模型训练、评估与调优经验。 4. 大模型工程化：掌握大模型微调技术（如 SFT、LoRA、P-Tuning、RLHF），能完成模型适配与优化；深入理解并实践 RAG、Prompt Engine…
登录查看完整任职要求
微信扫码，1秒登录
工作职责
1. 负责大模型在业务场景中的架构设计与工程化落地，综合运用RAG、AI Agent、Function Calling、Prompt Engineering等技术，构建端到端AI应用，包括知识库构建、向量检索集成、AI工作流编排及与业务系统的深度对接。 2. 负责大模型的生命周期工程管理，基于百炼、ModelScope、Hugging Face 或 LLaMA-Factory 等平台，开展模型微调（SFT/LoRA/P-Tuning/RLHF）、部署、监控与持续迭代； 3. 设计并实现面向业务目标的自动化评测体系，结合人工评估与自动指标（如F1、BLEU、ROUGE及业务定制指标），驱动数据闭环与模型迭代。 4. 开发高可用、高并发的应用服务，通过优化推理API性能、缓存策略与系统架构，保障服务稳定性与可扩展性。 5. 能够跨职能协同产出，与产品、UI/UX、测试及运维等团队紧密协作，推动AI功能从原型验证到规模化上线的全链路交付。
包括英文材料
学历+
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
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.
Spring Boot+
https://spring.io/guides/gs/spring-boot
his guide provides a sampling of how Spring Boot helps you accelerate application development.
https://www.youtube.com/watch?v=Nv2DERaMx-4&list=PLzUMQwCOrQTksiYqoumAQxuhPNa3HqasL
The author teaches you how to use Spring Boot from a complete beginner, to building a REST API with a real database, Dockerising it and deploying it to the cloud.
Gin+
https://gin-gonic.com/en/docs/quickstart/
This guide walks you through installing Gin, setting up a project, and running your first API—so you can start building web services with confidence.
https://go.dev/doc/tutorial/web-service-gin
This tutorial introduces the basics of writing a RESTful web service API with Go and the Gin Web Framework (Gin).
Django+
https://www.youtube.com/watch?v=nGIg40xs9e4
Learn how to build a simple Django application in as fast as 20 minutes!
https://www.youtube.com/watch?v=rHux0gMZ3Eg
Learn Django and start building amazing back-ends!
MySQL+
https://juejin.cn/post/7190306988939542585
这是一篇 MySQL 通关一篇过硬核经验学习路线，包括数据库相关知识，SQL语句的使用，数据库约束，设计等。
[英文] MySQL Tutorial
https://www.mysqltutorial.org/
your go-to resource for mastering MySQL in a fast, easy, and enjoyable way.
https://www.youtube.com/watch?v=5OdVJbNCSso
MySQL SQL tutorial for beginners
https://www.youtube.com/watch?v=7S_tz1z_5bA
This beginner-friendly course teaches you SQL from scratch.
PostgreSQL+
[英文] PostgreSQL Tutorial
https://neon.com/postgresql/tutorial
This PostgreSQL tutorial helps you quickly understand PostgreSQL.
[英文] PostgreSQL Tutorial
https://www.pgtutorial.com/
This PostgreSQL tutorial will teach you about PostgreSQL from beginner to advanced.
https://www.youtube.com/watch?v=qw--VYLpxG4
It is the most advanced open source database system widely used to build back-end systems.
https://www.youtube.com/watch?v=SpfIwlAYaKk
Learn PostgreSQL, one of the world's most advanced and robust open-source relational database systems.
Redis+
[英文] Developer Hub
https://redis.io/dev/
Get all the tutorials, learning paths, and more you need to start building—fast.
https://www.runoob.com/redis/redis-tutorial.html
REmote DIctionary Server(Redis) 是一个由 Salvatore Sanfilippo 写的 key-value 存储系统，是跨平台的非关系型数据库。
https://www.youtube.com/watch?v=jgpVdJB2sKQ
In this video I will be covering Redis in depth from how to install it, what commands you can use, all the way to how to use it in a real world project.
缓存+
https://hackernoon.com/the-system-design-cheat-sheet-cache
The cache is a layer that stores a subset of data, typically the most frequently accessed or essential information, in a location quicker to access than its primary storage location.
https://www.youtube.com/watch?v=bP4BeUjNkXc
Caching strategies, Distributed Caching, Eviction Policies, Write-Through Cache and Least Recently Used (LRU) cache are all important terms when it comes to designing an efficient system with a caching layer.
https://www.youtube.com/watch?v=dGAgxozNWFE
高并发+
https://www.baeldung.com/concurrency-principles-patterns
In this tutorial, we’ll discuss some of the design principles and patterns that have been established over time to build highly concurrent applications.
https://www.baeldung.com/java-concurrency
Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.
https://www.oreilly.com/library/view/concurrency-in-go/9781491941294/
You’ll understand how Go chooses to model concurrency, what issues arise from this model, and how you can compose primitives within this model to solve problems.
https://www.oreilly.com/library/view/modern-concurrency-in/9781098165406/
With this book, you'll explore the transformative world of Java 21's key feature: virtual threads.
https://www.youtube.com/watch?v=qyM8Pi1KiiM
https://www.youtube.com/watch?v=wEsPL50Uiyo
Prompt+
https://cloud.google.com/vertex-ai/generative-ai/docs/learn/prompts/introduction-prompt-design
A prompt is a natural language request submitted to a language model to receive a response back.
https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering
These techniques aren't recommended for reasoning models like gpt-5 and o-series models.
https://www.youtube.com/watch?v=LWiMwhDZ9as
Learn and master the fundamentals of Prompt Engineering and LLMs with this 5-HOUR Prompt Engineering Crash Course!
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
Prometheus+
https://grafana.com/docs/grafana/latest/getting-started/get-started-grafana-prometheus/
Prometheus is an open source monitoring system for which Grafana provides out-of-the-box support.
https://prometheus.io/docs/tutorials/getting_started/
Prometheus is a system monitoring and alerting system.
Grafana+
CI+
https://www.ibm.com/cn-zh/think/topics/continuous-integration
持续集成 (CI) 是一种软件开发实践，开发人员在整个开发周期中会定期将新的代码和代码变更集成到中央代码存储库中。它是 DevOps 和敏捷方法的关键组成部分。
https://www.youtube.com/watch?v=42UP1fxi2SY
CD+
https://www.redhat.com/zh-cn/topics/devops/what-is-ci-cd
CI/CD 是持续集成和持续交付/部署的缩写，旨在简化并加快软件开发生命周期。
https://www.youtube.com/watch?v=R8_veQiYBjI&list=PLy7NrYWoggjzSIlwxeBbcgfAdYoxCIrM2
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.
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.
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
Go+
https://www.youtube.com/watch?v=8uiZC0l4Ajw
学习Golang的完整教程！从开始到结束不到一个小时，包括如何在Go中构建API的完整演示。没有多余的内容，只有你需要知道的知识。
还有更多 •••
相关职位
社招5年以上云智能集团
作为**知识工程师（Knowledge Engineer，KE）**，你将站在技术与用户之间的关键交汇点，成为阿里云和通义产品技术知识体系的“翻译者”与“构建者”。你不仅是文档的撰写者，更是用户视角的深度洞察者、产品理念的精准传递者，以及AI时代下内容生产范式的革新者，用世界级的内容，点亮每一个用户的云之旅。 在这个角色中，你将融合传统内容运营、技术写作与AI工程的多重能力，基于大模型驱动的内容生成新范式，重构从“技术理解”到“用户认知”的全链路体验。你所产出的不只是文档，而是帮助用户快速上手、深入理解、高效决策的认知工具——让复杂的云架构变得可读、可感、可行动。 ‒ 按照集团技术内容规范与标准，为产品编写面向客户的技术文档，包括但不限于产品介绍、用户操作指南、教程、最佳实践、故障排除、开发指南、API/SDK参考等； ‒ 为技术文档编写必要的示例代码，帮助客户更快地了解产品能力； ‒ 通过开展调研和分析获取用户洞察，并据此制定内容改进方案，以提升技术文档质量； ‒ 深刻理解大模型原理，以构建agent 的方式，将AI 应用到技术文档的生产流程； ‒ 维护编写、改进和发布文档的风格指南和最佳实践。
更新于 2025-12-16北京|杭州
社招3年以上
主导AI技术研发全生命周期管理，包括需求分析、技术方案可行性评估、研发里程碑把控及交付验收，关注AI技术模块的研发进度与质量; 参与技术架构设计评审，协调算法、数据、工程化团队资源，确保数据/人力资源的最优配置; 建立AI研发专项风险管理机制，预判技术实施风险（如模型训练偏差、数据质量缺陷、性能瓶颈等）并制定应对方案; 搭建跨部门技术协作网络，推动产品、算法、运维团队建立高效协作机制，主导关键技术决策的跨部门对齐; 优化AI研发管理体系，完善模型迭代、AB测试、持续集成等关键环节; 负责技术文档质量管控，确保研发概要/详细设计等技术交付物的专业性与完整性.
更新于 2025-04-09上海
社招8年以上
1.负责包括android智能终端的语音/图像/大模型等AI算法工程化与系统级服务的开发和落地 2.负责AI交互基础原子能力如识别、人脸、多模态等算法引擎集成和效果优化工作 3.负责面向多终端的端云交互SDK设计和开发 4.负责AI相关算法与服务全链路性能分析和问题定位工具开发 5.负责端侧大模型推理引擎及上层应用的架构设计，集成和性能优化工作 6.撰写和维护架构设计文档、技术文档,保证框架设计的合理性评估,提升团队跨部门沟通协作效率 7.制定、实施统一的代码规范和质量标准,推动团队提升代码质量 8.跟踪及洞察技术趋势,根据业务需要及时输出技术调研报告
更新于 2025-04-16重庆
社招3年以上技术类-质量保证
•负责AI客服、AI培训、AI质检等产品的质量保障工作，参与产品的需求和架构设计评审、评估技术架构合理性和可测试； •构建适合业务发展的质量保障体系，推进质量分析和改进，通过数据、流程、策略、方法和工具等创新，提升测试质量和效率，保障产品高质量交付； •通过线上监控建设、用户行为，业务和技术指标分析，问题跟踪定位能力建设保障线上服务稳定性及驱动用户体验不断提升； •通过业务全链路数据分析、效果评测、竞品分析等手段帮助业务找到目标达成路径的核心问题，驱动解决，赋能业务；
更新于 2025-06-04杭州|成都