Machine Learning Engineer

We expect knowledge of:

- strong fundamentals of machine learning

- types of ml problems: classification, regression, clustering, etc

- common evaluation measures: precision, recall, F1, IoU, ROUGE etc

- scikit-learn models (random forest, SVM, xgboost), ensemble models etc.

- understanding dimension reduction techniques (PCA, TSNE, Umap)

- data preparation and visualization libraries (pandas, matplotlib etc.)

- knowledge of current neural networks architectures (RNN, CNN, Transformers) and methods (transfer learning)

- documented experience with one of library: PyTorch or Tensorflow

- good knowledge of relational databases and experience with one of : PostgreSQL, MySQL, MS SQL, Oracle

- good communication skills in English (minimum B2)

Depending on your role and experience

For NLP engineer:

- knowledge of modern word/sentence/document embedding methods (Word2Vec, BERT, Doc2Vec, Laser, etc.)

- knowledge of a classic bag of words approach (TF-IDF),

- experience with NLP libraries as: Hugging Face Transformers, Zalando Flair, NLTK,

- has documented experience with working with one of the problems: named-entity recognition, text summarization, topic modeling, tagging the parts of speech, text semantic similarity, neural search

For CV engineer:

- practical knowledge of OpenCV or related library

- knowledge of algoritmic (traditional) CV techniques like: Edge Detection, image features (Haar, HoG, SIFT, SURF etc)

- experience with implementing Convolutional NN or other image related neural architecture in Pytorch or Tensorflow,

- has documented experience with working with one of the problems: object classification, object tracking and detection, semantic segmentation, Pose Estimation,

For Recommender Systems engineer:

- has knowledge and experience with Collaborative filtering or Content-based filtering algorithms

- has knowledge about recomendation measures: MAP, MAP@K etc

- understanding od different similarity measures like: cosine similary, metric based similarity,

- has documented experience with working on project using recommendation engine

- has experience in one of library for efficient similarity search and clustering of dense vectors like: FAISS, Google Scan etc

Python and software development practices:

- experience in Python 3.x

- experience in using code versioning tools, such as Git

- day-to-day work experience with Docker