We are looking for data scientists that are passionate about applied and theoretical research in the realm of computational linguistics. As a data scientist, you will join us on our quest to develop novel approaches for generalized AI that can understand and generate natural language. As such, you will study linguistics and mathematical phenomena in order to create new state-of-the-art NLP models that can be applied on, and generalize across multiple domains and use cases.
Requirements:
Master degree or higher in Computer Science/Mathematics/Physics,/Electric engineering or equivalent is a must.
Strong theoretical background in Machine Learning.
An understanding of linguistics theory and principles (semantic relations, parsing methods, etc.).
2+ years experience with Python.
3+ years experience with conducting NLP research (Specifically: Text) using Deep Learning models (RNN, Transformers, etc) and frameworks (PyTorch, Tensorflow, etc.).
Educate our customers on new and existing features, best practices, and a variety of use cases across industries. This is achieved by planning and hosting online demos, consultations, and screen shares on both a one-to-one and one-to-many basis.
Master degree or higher in Computer Science/Mathematics/Physics,/Electric engineering or equivalent is a must.
Strong theoretical background in Machine Learning.
An understanding of linguistics theory and principles (semantic relations, parsing methods, etc.).
2+ years experience with Python.
3+ years experience with conducting NLP research (Specifically: Text) using Deep Learning models (RNN, Transformers, etc) and frameworks (PyTorch, Tensorflow, etc.).
Educate our customers on new and existing features, best practices, and a variety of use cases across industries. This is achieved by planning and hosting online demos, consultations, and screen shares on both a one-to-one and one-to-many basis.
An in-depth understanding in one or more of the following will be a plus:
Optimization.
Information theory.
Probability and statistics.
Bayesian methods.
Publications at top-tier conferences (i.e, ACL, EMNLP, ICML, NeurIPS).
Experience with distributed DL.
Experience with cloud ML (GCP, AWS, etc.).
This position is open to all candidates.
