Bloomreach is hiring a Senior Machine Learning Engineer / Data Scientist

Bloomreach is seeking a seasoned Senior Machine Learning Engineer to own the design and implementation of cutting-edge AI and GenAI driven algorithmic components for contextual personalization, predictions and behavioral insights that are used to personalize digital experiences for our customers. We are currently allowing flexibility for our employees to work from anywhere for the respective region (Central & Eastern Europe) or we are happy to meet you in our offices in Bratislava (Slovakia) or Brno, Prague (Czechia) on a full-time basis. Your Responsibilities: - Design, develop, and enhance ML/AI models which Predictions, Contextual Personalization and our new agentic workflows - Process historical data, product catalog and user behaviours to extract hidden relations and features. - Conduct research to explore ongoing cutting-edge ML techniques and conduct a quick POC. - Work closely with ML Engineers to integrate and scale ML components to a production-level that can handle terabytes of data. - Continuously learn and stay up to date with the current state-of-the-art techniques by reading research papers and attending AI/ML conferences. Qualifications: - BS/MS degree in Computer Science or a related discipline with a strong mathematical foundation and excellent programming skills (primarily Python) - At least 3 years of experience building ML-driven fast and scalable ML/analytical algorithms in a corporate/startup environment. - Strong awareness and understanding of recent trends in Generative AI and LLMs. Experience in working with GenAI stack will be treated as strong credentials. - Strong understanding of various machine learning and natural language processing technologies, such as classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking. - Excellent exploratory data analysis skills with the ability to slice and dice data at scale using SQL in BigQuery. - Good problem solving and analytical skills. Ability to learn and adapt to newer ML technologies. - Exposure to deep learning stack (PyTorch/Keras/TensorFlow) and techniques (Representation/Transfer Learning, RNN/LSTM, Transformers). - Experience working with Big Data in a cloud based production environment (AWS/GCP/Azure). - Effective communication skills in English, both verbally and in written form.