About Us:
Join us at Shanda AI Research as we are dedicated to becoming a global leader in AI innovation, driving the transition of AI technology from the copilot era to the autopilot era. We focuses on cutting-edge research in large models and next generation intelligent agents. Our mission is to push the boundaries of AI technology, develop groundbreaking models, and advance their real-world applications and impact.
Key Responsibilities:
- AI Innovation & Integration: Advance LLMs, LMMs, and next-gen AI by integrating long-term memory, retrieval-augmented generation (RAG), and intelligent agents.
- Implement and experiment with LLMs, multimodal models, and reasoning frameworks
- Build research prototypes for RAG, tool-use agents, and agentic learning systems
- Design and run controlled experiments for model reasoning, robustness, and trustworthiness
- Develop evaluation benchmarks and testing pipelines for AI systems
- Analyze model behaviour and propose improvements based on empirical findin
Industry Insight: Stay ahead of emerging AI trends, technologies, and applications that shape industries and transform businesses. Apply theoretical breakthroughs to real-world business challenges, driving AI adoption and impact.
Essential Qualifications:
1. Technical Expertise
- Strong understanding of Natural Language Processing (NLP), Computer Vision, Deep Learning, and Machine Learning.
- Familiarity with state-of-the-art models, including Autoregressive Language Models, Vision Transformers, and Diffusion Models.
- Proficiency with AI frameworks like PyTorch and experience in Retrieval-Augmented Generation (RAG) and intelligent agent systems.
2. Academic & Research
- Proven research experience with publications in top conferences and journals, such as ICLR, ACL, EMNLP, CVPR, NeurIPS, ICML, etc.
- Experience in developing and refining large-scale language models and visionlanguage models is a significant advantage.
3. Soft Skills
- Strong skills in communication, teamwork, problem-solving, and self-motivation.
Preferred Qualifications:
- PhD in Computer Science, Artificial Intelligence, or a related field. Demonstrated success in high-impact AI competitions or large-scale research projects.
Bonus Skills:
- Hands-on experience with large-scale data processing and deployment of deep learning models in production environments.
- Strong mathematical foundation and proficiency in both written and spoken Chinese and English, to support technical documentation and cross-functional communication.
