- Strong knowledge in machine learning fundamentals i.e. linear models, decision trees, naïve bayes, clustering algorithms, dimensionality reduction (PCA, t-SNE) and a good grasp of the strengths and weaknesses of specific approaches. Good foundation in basic statistics and linear algebra;
- Strong Python knowledge;
- Strong practical experience with Deep Learning frameworks like PyTorch, Tensorflow or Keras;
- At least minor experience with python visualization tools(matplotlib/seaborn, Plotly);
- Comprehensive knowledge of the Python data analyses ecosystem (Pandas, Numpy, Scikit-learn etc.);
- At least minor experience with natural language processing;
- Experience working in Linux, Unix environment.
As a plus:
- Experience with Tranformers architecture (GPT-2, BERT, etc);
- Understanding SOTA approaches for machine learning problems in NLP domain;
- Experience of work with LSTM models.
- 40-hour workweek with flexible working hours (start from 8 to 11 am);
- Annual paid vacations (18 working days);
- Paid days off on National Holidays;
- Paid sick leaves (10 working days);
- Possibility to work 2 days per month remotely;
- English classes (for different levels of language skills; etc.);
- External and internal professional trainings and conferences;
- Continuous learning opportunities and personal development plan;
- Tax compensation (Social & Single Social Payment) and accounting support;
- Engaging working process with challenging tasks in a professional environment;
- Open-minded, collaboration-friendly, invention-driven team;
- Corporate and team events.
- Participate in a massive NLP project from the early prototype stage;
- Research and implement approaches to improve project result quality and optimize speed;
- Move from prototype to production, ensuring scalability of models training and models inferring.