Technical Researcher

Responsibility

Lead research and development of core AI technologies, including machine learning algorithm design, deep learning model optimization, large language model training and deployment, and AI system architecture design.
Explore AI application scenarios in vertical domains (e.g., 5/6G, Web3.0, education, healthcare, legal, finance, AI4Science), design end-to-end solutions, and drive implementation validation.
Spearhead development of AI platforms and tools, covering full-chain technical challenges including data governance, model training, inference acceleration, and automated evaluation.
Facilitate cross-team collaboration, promote industry-academia cooperation, open-source community contributions, academic paper publications, and patent portfolio development.
Complete other tasks assigned by the leadership.

Requirements

Full-time master's degree or above in Computer Science, Mathematics, Statistics, Artificial Intelligence, or Data Science. Open-source community contributors is a plus.
Strong theoretical foundation in machine learning and deep learning, familiar with mainstream algorithms (CNN/RNN/Transformer/GAN). R&D experience in computer vision (CV), natural language processing (NLP), large language models, or reinforcement learning.
Proficient in TensorFlow/PyTorch frameworks and Python/C++ programming languages. Engineering experience in distributed training, model compression, and edge-side inference required. Large language model development experience (including MMLLM) is a plus.
Practical experience in integrating AI with vertical domains (5/6G, Web3.0, education, healthcare, legal, finance, AI4Science).
Excellent communication and coordination skills with fluent English proficiency (written and spoken) for daily research activities.