Senior/ Machine Learning Engineer(NLP)

About PatSnapPatsnap empowers IP and R&D teams by providing better answers, so they can makefaster decisions with more confidence. Founded in 2007, Patsnap is the global leaderin AI-powered IP and R&D intelligence. Our domain-specific LLM, trained on ourextensive proprietary innovation data, coupled with Hiro, our AI assistant, deliversactionable insights that increase productivity for IP tasks by 75% and reduce R&Dwastage by 25%. IP and R&D teams collaborate better with a user-friendly platformacross the entire innovation lifecycle. Over 15,000 companies trust Patsnap toinnovate faster with AI, including NASA, Tesla, PayPal, Sanofi, Dow Chemical, andWilson Sonsini.
About the roleWe are looking for machine learning engineers to help us improve various businessoutcomes and drive innovation. You will join a multidisciplinary team helping toshape our Product development. This is an excellent opportunity to take advantageof emerging trends and technologies to a real-world difference.

Responsibilities

• Responsible for exploring NLP-related cutting-edge technologies and applying them to search senario and AI agent senario.
• Responsible for analysing and understanding of the massive structured and unstructured data by NLP tasks, such as data processing, NER, relationship extraction, etc.
• Responsible for developing and fine-tuning models to meet business requirements.
• Work with a cross functional team to achieve business goals.

Requirements

• Minimum Qualifications
• Master or Bachelor degree in Computer Science, AI, or related field.
• Excellent coding ability, data structure and basic algorithm foundation.
• Proficient in C/C++ or Python.
• Familiar with NLP-related algorithms and technologies.
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• Preferred Qualifications
• Familiar with at least one field among ML, NLP, LLM, etc.
• Experience in using deep learning frameworks like PyTorch & TensorFlow.
• Experience in LLM, abstract, NER, or prompt engineering tuning, instruction, fine-tuning.
• Experience in optimising pre-trained models, familiar with BERT and GPT-based papers published in ACL/AAAI/KDD/NIPS/CVPR.
• Good communication and collaboration skills, able to explore new technologies with the team and promote technological progress.
• Excellent problem analysis and problem-solving skills, able to deeply solve the problems existing in LLM.