IPwe is a well-funded global team that is building the world’s first platform for intellectual property (IP) analytics and transactions. With over 15M active patents in the world from 200 national patent offices and patents multiple languages, IPwe has unique challenges in helping the world discover patents. You will build leading edge technologies that will bridge commercial language and patent language and help further innovation for the patent ecosystem. You will have the opportunity to work with leading experts in IP, AI and blockchain and to interact with some of the most innovative companies in the world. More information on IPwe is available at www.ipwe.com.
We are looking for a highly motivated scientist with a strong background in Natural Language Processing (NLP) and Machine Learning (ML). This position provides a unique opportunity to apply and develop cutting-edge and pioneering methodologies to language technology challenges and opportunities in the intellectual property space (patents, scientific literature, technical publications) and technology commercialization arena. The primary responsibility of this role is to formulate, engineer, and deploy innovative NLP and ML solutions in the IPwe platform as it relates to patent discovery and valuation.
Academic / Industry experience in NLP and ML, or similar experience in developing language technologies.
Familiarity with NLP and ML tools and packages, including deep neural network-based frameworks.
Practical experience building production quality applications related to NLP and ML.
In-depth knowledge of ML algorithms and ability to apply them in data driven NLP systems.
Ability to quickly prototype ideas / solutions, perform critical analysis, and use creative approaches for solving complex problems.
Ability to collaborate closely with cross-functional teams and lead a group of developers
Clear oral and written communication.
Fluent in English.
If you do a good job during the internship, then you will receive a full-time offer.
Education & Experience
Masters / PhD in Machine Learning, Statistics, Computer Science, Mathematics, Electrical Engineering, Data Science or a related field with specialization in natural language processing and/or machine learning.
Location: Remote (You can live anywhere in the world.)
Primary Work Premise: Home
Training Provided: Yes.
Travel Required: No
Please upload CV (in English)
Interview format: Video interview via Zoom or Microsoft Teams will be arranged upon selection notification