Company IntroductionPatSnap is a a SaaS-based tech innovation intelligence service provider.Patsnap helps R&D leaders to maximise the value of innovation intelligencewithin their R&D workflow and strategic planning. As the global leaders inconnected innovation intelligence, PatSnap use AI-powered and machinelearning technology to comb through billions of datasets, and help innovatorsconnect the dots. Patsnap recently completed a Series E funding round of $300million, led by Tencent and the SoftBank Vision Fund II. This represents thelargest round of funding in the SaaS sector since 2020, Patsnap is a unicorn inthe SaaS track.
Department IntroductionThe R&D SG Department is dedicated to building leading capabilities in naturallanguage processing technology and services. This is achieved by leveragingtechnologies such as Deep Learning, NLP, CV, and Knowledge Graph to createtop-tier products.
Job descriptionWe are looking for an experienced Senior Natural Language ProcessingEngineer to help us improve various business outcomes and drive innovation.You will join a multidisciplinary team helping to shape our Product development.This is an excellent opportunity to take advantage of emerging trends andtechnologies to a real-world difference.

Responsibilities

• Utilise natural language processing, machine learning, and data mining technologies to build models to achieve business objectives
• Proficient in using NER and relationship extraction to solve business problems
• Study and transform various kind of structured and unstructured data
• Organising data in to usable formats
• Enhancing the data collection process
• Create visualisations of data
• Analysing unstructured data using basic NLP techniques and extract important fields
• Develop NLP systems according to requirements
• Perform statistical analysis of results and refine models
• Remain updated in the rapidly changing field of machine learning
• Deploy models, optimise inference speed, and processing big data

Requirements

• Familiar with at least one field among ML, NLP, Knowledge Graph, LLM， and up-to-date with industry and academic progress
• Solid foundation in algorithms and have passion for technology development and application
• Proficient in programming languages such as Python, and has a good grasp of deep learning frameworks like PyTorch, and TensorFlow
• Familiar with name entity recognition and relationship extraction
• Experience in optimising pre-trained models, such as bert and gpt-based papers published in ACL/AAAI/KDD/NIPS/CVPR and other conferences will be preferred.