NLP Engineer

— Strong knowledge and practical experience in Natural Language Processing (NLP) area, i.e. TF-IDF, word embedding, Word2vec, Transformers, BERT;
— Good knowledge in machine learning i.e. clustering algorithms, dimensionality reduction (PCA, t-SNE). A good foundation in basic statistics and linear algebra;
— Strong Python knowledge;
— Comprehensive knowledge of the Python data analyses ecosystem (Pandas, NumPy, Scikit-learn, etc.);
— At least minor experience with python visualization tools (Matplotlib/Seaborn, Plotly);
— Strong practical experience with NLP frameworks: fastText, spaCy;
— Experience with following neural network architectures: LSTM, GRU and other RNN-based, XLM-RoBERTa
— Strong practical experience with Deep Learning frameworks like PyTorch, MXNet, TensorFlow, or Keras;
— Intermediate level of English.