Informacje o stanowisku

What We Expect:

• Experience in mentoring and delegating tasks within a team
• Strong communication skills and a desire to develop leadership competencies
• Proficiency in Python
• 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 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 in developing solutions based on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), building intelligent agents, applying methodologies like MCP, 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 experience with CI/CD, Linux fundamentals, and Docker
• Experience in building MLOps processes: automating the ML model lifecycle (training, deployment, monitoring), managing data and model versioning (MLflow, DVC), setting up pipelines (Kubeflow, Airflow), and conducting A/B testing
• Experience using Git for code version control and collaboration
• A Bachelors or Masters degree in Computer Science, Data Science, Mathematics, Statistics, or related fields
• Teamwork skills with product managers, data analysts, and business leaders
• Proficiency in English and/or German (and other languages) at a level not lower than B2

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 practical experience in using them

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