滴滴AI Selection 算法实习生

1. 数据“蒸馏”算法： 研发主动学习（Active Learning）与核心集选择（Core-Set Selection）算法，从PB级数据中自动化地“炼”出信息密度最高的“黄金数据集”，实现训练成本与模型性能的最优平衡。 2. 难例（Hard-Case）挖掘算法： 构建多模态难例挖掘引擎，融合图像、点云与模型内部状态，主动“捕获”长尾和边缘场景，持续拓宽模型的能力边界。 3. 算法归因与可解释性（XAI）： 基于可解释性AI与因果推断，开发自动化归因工具链。当模型失效时，能精准定位根因是来自数据、标注还是模型自身，实现从“现象”到“根因”的穿透。

职责模块：•System Architecture:; 职责描述:•Design and oversee end-to-end software architecture for embodied AI in home robots. •Define interfaces and protocols for system components. •Manage sensor and camera data for informed AI decision-making. •Guide middleware, simulation, and tool selection. -维护数据集版本控制和文档编写。 -整合用户和产品的反馈，以改进数据。 - 与算法工程师、产品经理和其他团队合作。; 权重:50%。 职责模块：•Integration & Optimization:; 职责描述:•Ensure seamless integration across hardware, AI algorithms, and cloud services. •Profile, debug, and optimize system performance. •Establish best practices for development, testing, and deployment.; 权重:25%。 职责模块：•Collaboration:; 职责描述:•Work with hardware, data science, and product teams to align technical and product goals. •Cooperate with researchers to design and develop advanced algorithms for perception, reasoning, planning, human-robot interaction (HRI) and emotional intelligence; 权重:15%。 职责模块：•Strategic Input; 职责描述:•Contribute to long-term vision and planning. •Represent the lab at conferences and industry events.; 权重:10%。

• Lead the architecture, design, and development of intelligent agent systems that integrate LLMs with real-world applications. • Drive full-stack engineering implementation, including backend services, API integration, database design, and task orchestration. • Select and optimize system components such as message queues, middleware, vector databases, and caching frameworks to meet performance and scalability targets. • Work closely with product and research teams to translate AI agent logic (e.g., tool-use, planning, reasoning) into robust, production-grade systems. • Take ownership of system performance tuning, including concurrency handling, throughput optimization, and service reliability. • Guide the team through best practices in code quality, CI/CD pipelines, and system observability. • Build and lead a team of engineers to deliver high-quality agent-driven applications from prototype to deployment.

1.负责开发零件-功能-材料的三维关系网络建模工具，实现BOM的语义化解构（使用Neo4j/TigerGraph等）； 2.负责建立材料性能的多模态嵌入模型（机械/化学/电学属性的向量化表示）； 3.设计ASTM/DIN标准数据的自动化解析管道（PDF→结构化数据→特征向量）； 4.开发材料性能的跨标准对齐算法（如GB与ISO的弹性模量映射）； 5.构建基于强化学习的材料搜索系统（贝叶斯优化），对接行业10万亿级材料库； 6.开发基于组合优化的TCO模型； 7.创新嫁接Agent：训练跨领域材料类比模型（使用GNN+Transformer架构）。