As an NLP R&D Engineer you will have the key responsibility including but not limited to of researching and applying the latest trends in Natural Language Processing to our big data sets comprising of 120+ million patent documents and more. Responsibilities include planning and management of ETL statistical & textual analysis pipeline while creating meaningful features in our different products for our clients and stakeholders. The successful candidate also have a chance to lead and build up the team capabilities within PatSnap.
Key Qualifications
The successful candidate should have significant experience in the following areas:
• Master or Ph.D, research direction is Natural Language Processing
• Domain Knowledge in Natural Language Processing / Machine Learning / Data Mining
• Deep understanding in at least 3 of the following: Sentiment Analysis, Entity Extraction, Natural Language Understanding
• Strong knowledge on deep learning for NLP
• Experience with Word Disambiguation and Word Embeddings
• Experience with open-source NLP toolkits such as CoreNLP, OpenNLP, NLTK, Gensim, LingPipe, Mallet, etc.
• Strong understanding of text pre-processing and normalization techniques, such as tokenization, POS tagging and parsing and how they work at a low level.
• Proficiency with common used programming languages such as C, C++, Python, Java and R
• Expertise in producing, processing, evaluating and utilizing training data
• Knowledge of Software Engineering best practices and standards
• Experience working with engineers and product managers
• Ability to present research progress to senior management
The successful candidate will also have the following attributes: