AI Engineer (m/w/d)

Build AI/ML Solutions: Develop and implement AI/ML models to solve specific business problems, ranging from training predictive models to creating NL solutions like document classifiers or chatbots. You will use Azure Machine Learning for experiment tracking and model management, and write code (Python/SQL) for data processing and model training. Azure Cloud Implementation: Deploy AI solutions on Azure cloud infrastructure, setting up necessary resources such as Azure ML workspaces, Azure Functions or AKS for hosting models, and Azure Data Factory pipelines for data movement, following Devoteam’s and Microsoft’s guidelines for security and compliance. Data Preparation & Feature Engineering: Work with data engineers to gather and prepare datasets required for machine learning, contributing to data preprocessing steps, writing data transformation scripts, defining features, and handling data quality issues, utilizing PySpark and SparkSQL in Azure Databricks or Microsoft Fabric for large-scale data processing when needed. Experimentation & Model Tuning: Conduct rigorous experiments to improve model performance, by trying out different algorithms or model architectures, tuning hyperparameters, and evaluating results, leveraging Azure ML pipelines to automate training runs and compare metrics. Integration of AI Services: Make use of Azure’s AI services to accelerate development, incorporating pre-built AI capabilities via Azure Cognitive Services when appropriate instead of building from scratch. MLOps & Monitoring: Implement the basics of MLOps for the solutions you build, registering models, creating release pipelines for deploying them, and setting up monitoring (for both system performance and model accuracy drift over time). Collaboration & Documentation: Collaborate within a crossfunctional team, taking guidance from the Senior AI Engineer and Architect while also providing input based on your own expertise, participating in design discussions, sprint planning, and code reviews, documenting your work thoroughly to aid maintainability and knowledge transfer within the team and to clients’ IT teams.