Data & AI Engineer

We are looking for an experienced Data & AI Engineer to join our Data & AI team and work on real-world Machine Learning, advanced analytics and AI solutions across complex enterprise environments. At the core of this role is Data Science – understanding business problems, analyzing data, developing and evaluating Machine Learning models, and translating analytical results into solutions that create measurable business value.

You will also have the opportunity to work with modern AI technologies, including Generative AI, LLMs and RAG, and collaborate with Data and Software Engineers to bring Data & AI solutions from experimentation into production. For senior candidates, the role offers the opportunity to take technical ownership, mentor colleagues and contribute to solution design and presales.

What you'll do

Analyze business problems and identify opportunities for Data Science, Machine Learning and AI Explore, prepare and analyze structured and unstructured datasets Design, develop, train and evaluate Machine Learning and statistical models Perform feature engineering, model optimization and validation Develop solutions for use cases such as forecasting, anomaly detection, classification, prediction and optimization Define evaluation metrics, monitor model performance and continuously improve models Collaborate with Data and Software Engineers on data pipelines and production integration Contribute to Generative AI solutions, including LLM-based applications, RAG and semantic search Apply good practices for experiment tracking, model versioning and reproducibility Contribute to technical estimations, Po.

Cs and solution design What we're looking for 3+ years of professional experience in Data Science, Machine Learning or advanced analytics Strong understanding of statistics, probability and Machine Learning fundamentals Strong programming skills in Python and/or R Experience with data exploration, preprocessing and feature engineering Hands-on experience developing, validating and optimizing Machine Learning models Understanding of model evaluation and the complete ML lifecycle Experience with Generative AI, Large Language Models (LLMs), RAG and semantic search Strong analytical and problem-solving skills Ability to translate business problems into analytical and ML solutions Ability to communicate results to both technical and business stakeholders Professional working proficiency in English Experience in some of the following areas is an advantage: NLP, embeddings and vector databases Time-series analysis and forecasting Anomaly detection and recommendation systems Large-scale or distributed data processing, including Spark ML pipelines and MLOps practices Model versioning, monitoring and experiment tracking Experience taking Data Science or AI solutions from PoC to production You don't need experience in all of these areas.

We are primarily looking for strong Data Science fundamentals and the ability to apply statistical and Machine Learning methods to real business problems, combined with an interest in modern AI engineering.

What we offer

Work on complex, real-world Data Science, Machine Learning and AI projects Exposure to different industries, datasets and business problems Work with large datasets and modern Data Platform environments Ownership beyond experimentation and PoC development Close collaboration with Data Engineering, Software Engineering and Platform teams Opportunity to work with both traditional Machine Learning and emerging Generative AI technologies Continuous learning and professional development For senior candidates, opportunity to take technical ownership and mentor other team members