AI Research Engineer AI技术研究员

Responsibilities

Conduct research and development of core AI technologies, including machine learning algorithm design, deep learning model optimization, large-scale model training and deployment, and AI system architecture design;Explore the application of AI technologies in vertical domains (such as 5G/6G, Web 3.0, education, healthcare, law, finance, AI for Science, etc.), design end-to-end solutions, and drive implementation and validation;Lead the development of AI platforms and tools, covering the full technical stack including data governance, model training, inference acceleration, and automated evaluation;Collaborate across teams to promote industry-academia-research cooperation, contribute to open-source communities, publish academic papers, and participate in patent strategy planning;Complete other tasks assigned by leadership.负责人工智能核心技术研究与开发，包括机器学习算法设计、深度学习模型优化、大模型训练与部署，以及AI系统架构设计；探索AI技术在垂直领域（如5/6G，web3.0，教育，医疗，法律，金融，AI4Science等）的应用场景，设计端到端解决方案并推动落地验证；主导AI平台与工具的研发，涵盖数据治理、模型训练、推理加速、自动化评估等全链路技术攻关；开展跨团队协作，推进产学研合作、开源社区贡献、学术论文发表及专利布局；完成领导交办的其他任务。Requirements:Master’s degree or above from a full-time accredited institution in Computer Science, Mathematics, Statistics, Artificial Intelligence, Data Science, or related fields; contributions to open-source communities are preferred;Solid theoretical foundation in machine learning and deep learning; familiarity with mainstream algorithms and models (e.g., CNN, RNN, Transformer, GAN); experience in areas such as computer vision (CV), natural language processing (NLP), large models, or reinforcement learning is preferred;Proficient in frameworks such as TensorFlow or PyTorch, and programming languages like Python or C++; engineering experience in distributed training, model compression, and edge inference is a plus; hands-on experience in developing large models (e.g., LLMs or multimodal models) is preferred;Practical experience integrating AI with vertical industries (e.g., 5G/6G, Web 3.0, education, healthcare, law, finance, AI for Science) is a strong advantage;Excellent communication and coordination skills, with fluency in English (listening, speaking, reading, and writing) for daily research activities.全日制硕士或以上学历，计算机科学、数学、统计学、人工智能、数据科学等专业优先；具有开源社区贡献经验者优先；具备扎实的机器学习、深度学习理论基础，熟悉主流算法模型（如CNN/RNN/Transformer/GAN等），有计算机视觉（CV）、自然语言处理（NLP）、大模型，强化学习等领域研发经验者优先；熟练使用TensorFlow/PyTorch等框架，掌握Python/C++等编程语言，具备分布式训练、模型压缩、边缘端推理等工程化经验；具有大模型（如LLM、多模态模型）开发经验者优先；具备AI与垂直领域（如5/6G，web3.0，教育，医疗，法律，金融，AI4Science）结合的实践经验者优先；具备优秀的沟通和协调能力，具备流利的英语听说读写能力，可使用英文开展日常科研工作。