Senior Industrial Software Developer

Responsibilities:

Primary responsibilities for this position include:

• Knowledge Graphs

• Be responsible for the full-process research and development of knowledge graphs, including knowledge extraction (entity, relationship, attribute extraction), knowledge fusion, knowledge reasoning, knowledge storage and update, and build high-quality domain knowledge graphs.

负责知识图谱全流程研发，包括知识抽取（实体、关系、属性抽取）、知识融合、知识推理、知识存储与更新，搭建高质量领域知识图谱。

• Optimize the efficiency and accuracy of knowledge graph construction, address issues such as knowledge ambiguity and data noise, and support knowledge applications in scenarios like intelligent question answering, semantic retrieval, and decision support.

优化知识图谱构建效率与精度，解决知识歧义、数据噪声等问题，支撑智能问答、语义检索、决策支持等场景的知识应用。

• Design knowledge graph application solutions in combination with business scenarios, integrate generative AI with knowledge graphs, and enhance the accuracy, professionalism, and interpretability of model responses.

结合业务场景设计知识图谱应用方案，联动生成式AI与知识图谱，提升模型回答的准确性、专业性与可解释性。

• Embodied Intelligence

• Participated in the research and development of embodied intelligent agents, responsible for the design and development of modules such as environmental perception, action planning, task decomposition, and feedback learning, to achieve autonomous decision-making and execution of agents in specific scenarios.

参与具身智能Agent研发，负责环境感知、动作规划、任务拆解、反馈学习等模块的设计与开发，实现Agent在特定场景下的自主决策与执行。

• By integrating multi-modal inputs such as vision and voice, optimize the interaction capabilities of embodied intelligent systems, break through the closed loop of perception, cognition and action, and enhance the Agent's ability to adapt to complex scenarios.

结合视觉、语音等多模态输入，优化具身智能系统的交互能力，打通感知-认知-动作闭环，提升Agent适应复杂场景的能力。

• Keep up with the cutting-edge technologies of embodied intelligence (such as reinforcement learning, imitation learning, and multi-agent collaboration), implement technical solutions, and continuously iterate and optimize system performance.

跟进具身智能前沿技术（如强化学习、模仿学习、多智能体协作），落地技术方案并持续迭代优化系统性能。

• Generative AI

• Responsible for the fine-tuning, Prompt Engineering, and agent-based development of generative AI models (such as LLM large models, multimodal generative models, etc.) to meet the requirements of business scenarios.

负责生成式AI模型（LLM大模型、多模态生成模型等）的微调、Prompt Engineering、Agent化开发，适配业务场景需求。

• Build a generative AI application framework to address core issues such as model illusion, generation quality, and response speed, and support the implementation of business scenarios such as content generation, intelligent dialogue, and creative generation.

搭建生成式AI应用框架，解决模型幻觉、生成质量、响应速度等核心问题，支撑内容生成、智能对话、创意生成等业务场景落地。

• Explore the integration solutions of generative AI with knowledge graphs and embodied intelligence, build an integrated intelligent system, and enhance the depth and breadth of AI applications.

探索生成式AI与知识图谱、具身智能的融合方案，构建一体化智能系统，提升AI应用的深度与广度。

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Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.

Client-provided location(s): Shanghai, China

Job ID: Aptiv-J000695527

Employment Type: OTHER

Posted: 2026-03-31T21:10:46