Czym będziesz się zajmować? Responsibilities:Design, develop, and deploy Generative AI and machine learning solutions using platforms like Azure OpenAI Services, Google Vertex AI, Amazon Bedrock, or similar. Work in cross-functional agile teams to build end-to-end data science pipelines - from exploration and feature engineering to training, validation, and deployment. Investigate and analyze large, high-dimensional datasets, applying the latest AI/ML techniques to extract value. Implement, test, and evaluate algorithms for data processing, exploration, modeling, and insight generation. Build dashboards, apps, and reports to visualize model results and support business decision-making. Ensure autonomous development and documentation of reusable components, services, and workflows. Transfer knowledge and project results to internal business teams and external clients through clear documentation and workshops. Serve as a technical advisor during client engagements, identifying opportunities, recommending solutions, and sharing best practices.

Kogo poszukujemy? Requirements:MSc in Artificial Intelligence, Data Science, Computer Science, Engineering, Mathematics, Physics, Statistics, or a related field. 4+ years of hands-on experience in data science or applied machine learning roles.Strong experience with Generative AI platforms (e.g., Azure OpenAI, Google Vertex AI, Amazon Bedrock, Amazon Titan). Deep understanding of various ML techniques, including: Regression, Decision Trees, Ensemble Methods Deep Neural Networks (DNN), SVMs, Clustering, Reinforcement Learning Solid proficiency in Python (preferred) or other programming language, with working knowledge of ML and data processing libraries (e.g., scikit-learn, pandas, PyTorch, TensorFlow). Demonstrated ability to handle complex, high-volume, multi-source data effectively. Hands-on experience with data visualization tools (preferably Power BI, optionally Tableau). Practical experience with cloud ML environments (Azure, AWS, GCP); certifications are a strong plus. Familiarity with MLOps practices and deploying models into production environments. Strong communication skills and business orientation - able to translate technical outputs into strategic value. Proficiency in spoken and written English.