To be successful with projects you need to have:

• Strong proficiency in Python
• 2+ years of professional and commercial experience in Data Science, NLP, and Computer Vision (all or some) applied to solving business problems; familiarity with modern (SOTA) models and advanced approaches in the field
• Deep knowledge of ML/AI frameworks (TensorFlow, PyTorch, Scikit-learn), algorithms (supervised, unsupervised, reinforcement learning), and techniques (feature engineering, model optimization, hyperparameter tuning)
• Experience developing solutions based on large language models (LLM), Retrieval-Augmented Generation (RAG), building intelligent agents, applying MCP methodologies, and other modern AI approaches
• Understanding of big data platforms (Spark, Hadoop) and cloud services (AWS, Azure, Google Cloud) for scalable deployment
• Basic DevOps skills, including CI/CD, Linux fundamentals, and Docker
• Experience building MLOps processes: automating ML model lifecycle (training, deployment, monitoring), managing data and model versions (MLflow, DVC), pipeline orchestration (Kubeflow, Airflow), and A/B testing
• Experience using Git for version control and collaboration
• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or related fields
• Strong skills in collaboration with product managers, data analysts, and business leaders
• English and/or German (or other languages) proficiency at B2 level or higher

Will be a plus:

• Certifications in ML, Data Science, or cloud platforms (e.g., AWS Certified Machine Learning Specialty, Google Cloud ML Engineer, Microsoft Certified: Azure Data Scientist Associate)
• Knowledge of modern AI tools and hands-on experience applying them