Ontotext helps companies upgrade their data into knowledge! We thrive in the fields of cognitive computing by working extensively on knowledge representation and information extraction. To do that, we utilize the best achievements in machine learning and natural language processing, applying them in integrity with our own products – GraphDB and the Ontotext Platform.
Who are we looking for:
We are looking for a NLP Engineer who will strengthen our expertise in the development and implementation of NLP tools to analyze large datasets and who will add value to the development of semantic technology applications employing advanced hybrid methodologies. Оur applications are focused in the Life Sciences domain.
If you are a tech person and also interested in natural language and like to be challenged by interdisciplinary tasks – this position is for you!
As NLP Engineer you will:
Research state-of-the art approaches and toolkits for solving NLP problems;
Propose methodology for solving NLP problems;
Implement NLP solutions on Ontotext’s own and public platforms;
Train and evaluate NLP models;
Find, run and test algorithms for analyzing large datasets ensuring reproducibility and provenance – mainly related to pre-processing of resources for NLP;
Participate in customer meetings to provide technical expertise;
Collaborate with other NLP Engineers, Data Scientists and Software developers to define metrics, guidelines, and workflows;
Keep up-to-date knowledge of the rapidly changing field of NLP;
Engage with the R&D team to contribute to researching new technologies and developing of prototypes.
Work with the following technologies: GATE, Java, Python, Bash, SPARQL, GraphDB, GitLab, Maven, Jenkins, Linux, Docker .
You will work in a team of experienced NLP Engineers who will guide you through the principles and magic of text analysis. To walk the path with them you will need:
Aptitude to develop or further develop your NLP knowledge and skills;
Programming knowledge or experience, ideally in Java and/or Python, and desire to improve it;
Knowledge of OOP, Data Structures and Algorithms;
Experience/knowledge of computational linguistics will be a strong advantage;
Some experience in natural language processing tools and platforms (such as GATE, spaCy, OpenNLP, NLTK, CoreNLP, Gensim, UIMA) will be considered as a strong advantage;
Experience in the field of Healthcare and LifeSciences domain is preferred, but not mandatory;
Proactive and initiative-driven attitude;
Open to interdisciplinary tasks and collaboration;
English language – excellent, written and verbal.
Collaboration, opportunity to learn and exchange ideas with experienced NLP Engineers;
Chance to work on end-to-end solutions;
Dynamic environment, flat hierarchy and common-sense culture, where everyone’s voice is heard;
Exposure to new technologies, international companies, projects and teams.