You will need to have:

• Strong Python skills
• 3+ years of professional, commercial experience in developing and applying Data Science, NLP, and Computer Vision practices (some or all) to solve business problems; familiarity with state-of-the-art (SOTA) models and advanced approaches in these fields
• Deep knowledge of ML/AI frameworks (TensorFlow, PyTorch, Scikit-learn), algorithms (supervised, unsupervised, reinforcement learning) and techniques (feature engineering, model optimization, hyperparameter tuning)
• Experience in developing solutions based on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), building intelligent agents, applying MCP techniques and other modern AI approaches
• Understanding of working with big-data platforms (Spark, Hadoop) and cloud services (AWS, Azure, Google Cloud) for scalable deployment
• Basic DevOps skills, including working with CI/CD, Linux fundamentals, and Docker
• Experience in building MLOps processes: automating the ML model lifecycle (training, deployment, monitoring), managing data and model versions (MLflow, DVC), configuring pipelines (Kubeflow, Airflow), A/B testing
• Experience using Git for code version control and collaboration
• Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, or related disciplines
• Teamwork skills with product managers, data analysts, and business leaders
• Experience in mentoring and task delegation within a team
• Strong communication skills and a desire to develop leadership competencies
• Proficiency in English and/or German (and other languages) 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, or Microsoft Certified: Azure Data Scientist Associate)
• Knowledge of modern AI tools and experience using them in work