Understand business objectives and models that help achieve them
Propose and realize new ideas to benefit our customers and the company
Fully cover (develop, maintain, and monitor) the entire lifecycle of created models
Propose new research, improvements, and best practices
Share knowledge, ideas, and new approaches with team members
Stay up-to-date with the latest findings in applied data science

What You Should Bring

Must-have

Hands-on experience (3-6 years) developing machine learning solutions with Python for Unstructured Text Based Problems (NLP), including: ML problem analysis, data preparation (Exploratory Data Analysis) & transformation, feature analysis & selection, topic modelling & NER (Named Entity Recognition), ML model selection using parameter tuning, model result analysis and presentation, transfer learning, and developing custom ML models based on requirements
Excellent knowledge of Python + Java or C++
Knowledge of PyTorch/TensorFlow/Sagemaker/Docker/MLflow/Kubeflow/Linux, as well as knowledge in the latest neural networks (Transformers, LSTM, GAN, etc.)
Good knowledge of machine learning libraries (like Scikit-learn, NLTK, spacy, etc.)
Strong programming knowledge of Python, Flask, NumPy, Pandas, etc.
Good knowledge of statistics and algorithms
Experience in image recognition or OCR technology

Nice-to-have