Machine Learning Engineer (EU Candidates)

Hi there!

We are the biggest European Python Powerhouse with over 17 years of experience, 8 offices in Poland and deep commitment to Agile principles. Join a group of 500+ professionals dedicated to helping customers build outstanding products.

Are you the NEXT one?

“The data revolution has enabled us to create software solutions which mimic our intelligence behavior. I always wanted to be part of it by building data and artificial intelligence products. For my team I’m looking for those who are not afraid of challenges and want to solve difficult problems which eventually help people with use data engineering and machine learning. “
– dr Krzysztof Sopyła – Head of Machine Learning and Data Engineering



Regular+:up 20 160 zł + VAT

Senior:up to 28 560 zł + VAT


What do we need from you?

Core values

We believe that every problem has a solution, often hidden and not so obvious. Our job is to work out them and the best  are born from imagination, cooperation and being craftsmanship.

How do we work?

We work with clients for their benefit and the benefit of their target users. We often act as consultants and architects, people who tear down the existing order, introducing changes and innovations. But just as often we act as craftsmen who must deliver software of the highest quality.

How the daily work will look like?

You will be assigned to a team working on a project for one of our foreign clients. Your responsibilities will include developing, inventing and implementing solutions to process large or distributed data.

What is expected of you?

The role of a Machine Learning Engineer has many variations, we are not looking for someone who is good at everything, but people with in-depth knowledge of a particular domain of NLP, Computer Vision or Recommender systems. What is important to us is the foundation and basic understanding of the problems and ideas behind ML.We use ML methods in practice so we also value the ability to implement models in the form of API or integration with the client’s system.

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

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
    • more advanced python constructs as: lambda functions, generators, list comprehension etc
    • core principles of object-oriented programming
    • understanding of the threading and multi-process computation in Pyhon
  • experience in using code versioning tools, such as Git
  • day-to-day work experience with Docker

Soft skills:

  • good communication skills in English (minimum B2)
  • problem solving and analytical thinking
  • be nice and friendly

Your experience rating will also be affected by your other skills such as:

  • knowledge of at least one cloud platform (AWS, Azure, GCP) and its solutions related to data processing
  • background in at least one NoSQL database like HBase, DynamoDB, MongoDB, Cassandra
  • data scraping experience
  • experience in search systems like Elasticsearch, Jina AI etc.
  • experience in data engineering tools
  • other development skills like REST API or frontend skills