Grammarly NLP Team – This is the perfect time to join:

This is the perfect time to join: We’ve been investing in a mature ecosystem of language and language learning machines for over a decade, but because we are a growing company, individuals still have too much ownership. Want to overcome those barriers and improve human communication at scale? We are looking for talented and passionate people to join our grammar and NLP and ML infrastructure to leverage the latest advances in technologies such as transformation-based sequencing models, neural machine translation, and massive pre-trained language models. For example, we use models designed to work on a large server and port them to mobile with tradeoffs based on our knowledge of how people communicate on different devices. Computational and analytical linguists bring their knowledge of communication to our NLP problems, allowing us to combine linguistic rules and heuristics with large-scale statistical methods. Application scientists and machine learning engineers work together at Grammar in small, flexible teams. Another challenge is how to adapt this complex mechanism to the nuances of different communication domains. After all, human language is highly context dependent. Every day, the ML engineer works with researchers and linguists to examine data, conduct experiments based on customer feedback, or address the scalability and performance of the model. To make this possible, we’ve built a sophisticated portfolio of production models and a robust system for collecting, storing, and annotating large volumes of diverse data. Fortunately, we can prioritize zero-emission projects and move quickly from concept to launch because we’ve spent more than a decade building an ecosystem of linguistic and machine learning tools. Human communication is highly subjective and personal, posing a huge challenge to product, design and engineering. With more than a decade of experience developing an engaging communication assistant, we don’t just train a big linguistic model with deep neural networks to solve any problem. To achieve this contextual understanding at many stages of communication, general knowledge based on “Big Data” must be transformed into a purposeful experience for the individual user.