AI Research Engineer AI技术研究员

• 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.

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.