This opportunity is based in Lausanne

Active Learning Annotation Tool (Internship)



While the frontiers in natural language processing (NLP) research are rapidly expanding, it is still a great challenge to develop customized NLP solutions in the real world. Properly annotated data is scarce, making it impossible to train or even finetune data-hungry algorithms. In particular for named entity recognition (NER), accurate annotations are crucial but very expensive to gather. Even more so in the 3 Swiss national languages.

Active learning methods can mitigate the problem by facilitating the annotation task and reducing the work effort required by domain experts.

Within the scope of this internship, the student will leverage an active learning approach to develop an efficient annotation tool and integrate it into one of our existing NLP products. In addition, the application of NER to data anonymization will be studied and developed. This application is becoming rapidly pervasive with all data analytics services that require a certain level of privacy and security. Existing libraries have very good performance when it comes to NER for English documents, however for other languages, the performance drops, often drastically. Data anonymization systems need to rely on highly performant extraction models, with minimal leakage and having such a system

In this role


The goal of the internship is to:

  • Study and compare state-of-the-art active learning and named entity recognition (NER) methods. The student will have the opportunity to deepen their knowledge in these two fields.
  • Design and implement an active learning annotation tool to annotate text corpora for NER tasks. The intern will be able to sharpen their software development and ML engineering skills.
  • Integrate the tool into one of our existing products. The student will be responsible for the productification of their solution.

What we offer

INTERNSHIP in Lausanne. Join our team as intern and you will find a young, dynamic and culturally diverse working environment.

About your profile

  • Interest and strong knowledge in Machine Learning and Natural Language Processing
  • Experience with Python (NumPy stack, common ML and NLP libraries)
  • Experience with Git, Docker and REST/microservices is a plus

If you are INTERESTED in applying for this position, please send us your complete application (CV, cover letter, letter of reference, diplomas and certificates).

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