英伟达AI Application Developer

岗位概述 协助团队进行 AI 应用开发与大数据平台迭代，参与机器学习算法调研与工程化落地，提升平台数据处理与智能分析能力。 本岗位为 2026 年暑期实习，全职实习时长 5 个月以上。实习期间表现优秀者，将有机会获得留用。 职责描述 - 协助大数据平台的 AI 应用开发与迭代，提升平台数据处理与智能分析能力 - 协助处理海量业务数据，参与数据清洗、转换、特征提取等 AI 数据治理工作 - 参与机器学习算法（分类、回归、聚类、推荐等）的调研、调试与优化 - 配合正式员工完成 AI 相关技术验证、原型开发，参与团队技术讨论 - 跟进行业前沿技术（大数据处理、AI 应用、机器学习框架），并尝试应用到实际工作中 任职资格 - 本科及以上学历，计算机、大数据、人工智能、统计学、数学等相关专业 - 了解 Hadoop、Spark、Flink 等大数据处理框架的基本原理与使用方法 - 掌握 Python / Java 至少一种编程语言，能独立完成简单代码开发与调试 - 具备机器学习基础，了解常见算法（决策树、随机森林、SVM、逻辑回归、K-Means 等）的原理和适用场景 - 了解 AI 应用开发流程，了解 RAG 技术栈（向量数据库、LangChain 等） 加分项 - 有大数据或 AI 应用相关项目/实习经验 - 熟悉主流 AI 开发工具，能够利用 AI 辅助提升工作效率 ▸ Overview You'll support the team in building and iterating AI-powered platform features, from data pipeline work to ML algorithm research and engineering deployment. This is a full-time summer 2026 internship (5+ months). Strong performers will be considered for a return offer. ▸ Responsibilities - Develop and iterate AI features on the big data platform to improve intelligent analytics capabilities - Work with large-scale business data; participate in data cleaning, transformation, and feature extraction - Research, debug, and optimize ML algorithms (classification, regression, clustering, recommendation, etc.) - Support proof-of-concept development and participate in team technical discussions - Stay current with trends in big data and AI frameworks; apply new techniques to real work ▸

In this role, you will AI Solution Development: Design, develop, and deploy AI-driven applications, across domains, such as machine learning, NLP, and computer vision, addressing both business requirements and end-user needs. End to End Supply Chain Connectivity: Partner with supply chain experts to understand business goals and translate into clear technical specifications and solutions recommendation. Agent Design and Development: Design and implement intelligent agents within multi-agent systems, enabling real-time collaboration based on pre-defined goals, strategies, and data exchanges. Develop agent-based models to optimize decision-making and interactions. MCP Integration: Extend and integrate Multi-Agent Coordination Platforms(MCP) to optimize resource allocation, communication, and decision-making across multiple agents in shared environments. Data Management: Architect, design, build, and maintain data pipelines that connects across internal and external supply chain systems. Enforcing data governance and control is implemented at key matrix levels. Collaboration with Data Science Teams: Collaborate with data scientists to refine algorithms, optimize models, and enhance AI performance, focusing on model tuning, feature selection, and performance benchmarking. Testing and Validation: Conduct rigorous testing and validation of AI models, including unit testing, integration testing, and A/B testing, to ensure accuracy, reliability, and scalability before deployment. Monitoring and Maintenance: Monitor deployed AI models, track performance metrics, and implement continuous improvement strategies, including model re-training and updates based on real-world data and evolving business needs.

• In this role, you will • - AI Solution Development: Design, develop, and deploy AI-driven applications, across domains, such as machine learning, NLP, and computer vision, addressing both business requirements and end-user needs. • - Agent Design and Development: Design and implement intelligent agents within multi-agent systems, enabling real-time collaboration based on pre-defined goals, strategies, and data exchanges. Develop agent-based models to optimize decision-making and interactions. • - MCP Integration: Extend and integrate Multi-Agent Coordination Platforms(MCP) to optimize resource allocation, communication, and decision-making across multiple agents in shared environments. • - Collaboration with Data Science Teams: Collaborate with data scientists to refine algorithms, optimize models, and enhance AI performance, focusing on model tuning, feature selection, and performance benchmarking • - Testing and Validation: Conduct rigorous testing and validation of AI models, including unit testing, integration testing, and A/B testing, to ensure accuracy, reliability, and scalability before deployment. • - Monitoring and Maintenance: Monitor deployed AI models, track performance metrics, and implement continuous improvement strategies, including model re-training and updates based on real-world data and evolving business needs.

日常实习：面向全体在校生，为符合岗位要求的同学提供为期3个月及以上的项目实践机会。 团队介绍：火山方舟是火山引擎推出的一站式大模型服务平台，是中国大模型市场产品和份额领跑者。平台提供模型推理、评测、精调等全流程服务。方舟搭载了豆包及业界主流大模型，提供丰富的插件生态和AI应用开发服务，并通过稳定可靠的安全互信方案、专业的算法技术服务，全方位保障企业级AI应用落地。 1、负责AI搜推、知识库、记忆库、向量数据库等大模型技术在垂类行业应用场景需求收集及调研，参与方案设计； 2、负责配合产品解决方案人员推动AI搜推在电商导购、视频行业、新闻资讯及图搜等方向的客户沟通、落地及交付； 3、负责跟进重点客户，配合推动达成合作，树立行业标杆案例，梳理完善产品方案的行业最佳实践； 4、负责协助产品解决方案人员和产品同学进行项目管理，配合客户在接入及交付过程中的问题答疑； 5、负责基于行业需求和产品能力，完善和迭代见客材料。