About PatSnap
Patsnap empowers IP and R&D teams by providing better answers, so they can make faster decisions with more confidence. Founded in 2007, Patsnap is the global leader in AI-powered IP and R&D intelligence. Our domain-specific LLM, trained on our extensive proprietary innovation data, coupled with Hiro, our AI assistant, delivers
actionable insights that increase productivity for IP tasks by 75% and reduce R&D wastage by 25%. IP and R&D teams collaborate better with a user-friendly platform across the entire innovation lifecycle. Over 15,000 companies trust Patsnap to innovate faster with AI, including NASA, Tesla, PayPal, Sanofi, Dow Chemical, and
Wilson Sonsini.
Key Responsibilities
- Lead the development of cutting-edge NLP, ML, and LLM models to drive product innovation.
- For Data extraction, the implementation of NER and relationship extraction techniques for efficient, high-quality data construction.
- Guide the development of tailored NLP systems for specific use cases and requirements.
- Manage the deployment and optimization of ML models, focusing on inference speed and large-scale data processing efficiency.
- Spearhead initiatives in search engine technology and retrieval-augmented generation.
- Lead and mentor a team of NLP engineers, fostering innovation and tracking industry advancements.
Desired Qualifications
- Minimum of 5 years of professional experience in NLP, with a strong understanding of current industry and academic trends.
- Extensive knowledge of LLMs and proven leadership skills in managing teams of 5+ engineers.
- Fluency in English and Chinese, with excellent communication skills.
- Strong foundation in algorithms and a passion for technological innovation and application.
- Advanced proficiency in Python and deep learning frameworks such as PyTorch and TensorFlow.
- Expertise in named entity recognition and relationship extraction techniques.
- Demonstrated experience in optimizing pre-trained models, particularly BERT and GPT-based architectures.
- Publications in top-tier conferences (e.g., ACL, AAAI, KDD, NeurIPS, CVPR) are highly desirable.
- Master's degree in Computer Science, Computational Linguistics, or a related field; Ph.D. preferred.
