Описание: GEMA works to ensure that creative professionals receive a fair share of the revenue generated by the use of their musical works, allowing them to focus on their artistic work.
Задачи:
•Identify AI use cases with subject-matter experts, Product Owners, and technical teams, refine business questions, and develop viable approaches, including demos or prototypes where useful
•Work across the AI delivery lifecycle, from data analysis and feature engineering through model development, training, evaluation, and integration into usable services
•Select classical machine learning, deep learning, neural networks, LLM-based solutions, or a practical combination based on each use case
•Bring successful approaches into production-ready or production environments and consider deployment, monitoring, model and data quality, security, traceability, and maintainability from the start
•Contribute to and develop the AI Platform with the team, including components for MLOps, monitoring, labeling, evaluation, and deployment
•Take ownership of projects and work packages and collaborate closely with subject-matter experts, Product Owners, Software Engineers, and Data Engineers
Требования:
•Have several years of experience developing data- or AI-related applications and be able to advance AI solutions from initial concept to usable application
•Work independently and responsibly, and drive complex topics with a clear focus on results
•Explain complex technical topics clearly, justify solution approaches and model decisions, and present results confidently to business and technical stakeholders
•Be familiar with machine-learning and data-science workflows, including data analysis, feature engineering, model training, evaluation, and understanding model limitations
•Use Python and libraries or frameworks such as Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, and XGBoost, or comparable tools; assess classical ML, deep learning, and generative AI approaches for each use case
•Apply software engineering practices including Clean Code, testing, Git, Pull Requests, CI/CD, technical documentation, and maintainable architectures
•Have experience with cloud and MLOps topics
•Communicate confidently and precisely in German, both spoken and written, and use English confidently in a professional environment
Будет плюсом:
Google Cloud, Infrastructure as Code, GitHub Actions, model versioning, pipeline orchestration, monitoring, deployment of ML services
Условия:
•Part-time option: 30 hours per week
•30 days of vacation, flexitime, a home-office arrangement, and workation
•Subsidized company restaurant, barista bar, modern office in a prime location, capital-forming benefits, discounts, and other allowances
•Childcare subsidy, active breaks, pme family service, special leave, and flexible working arrangements
