scikit-learn Jobs in Austria

In this role, you will develop advanced ML models to optimize battery and renewable energy forecasts, oversee the entire model lifecycle, and support commercialization across various markets.

In this role, you will develop advanced ML models, optimize datasets, and manage the entire ML lifecycle from training to deployment using Python, PyTorch, and Docker, while collaborating closely with other teams.

In this role, you will develop advanced ML and deep learning models, manage the entire ML lifecycle, and implement MLOps practices to ensure reliable, scalable AI solutions.

In this role, you will design data projects and develop machine learning in Python. You will work on challenging customer projects, optimizing models while collaborating closely with engineers.

In this role, you will develop dashboards and applications using Python, prepare data, visualize KPIs, and implement solutions in close collaboration with management.

In this role, you develop LLMs and agentic applications, implement AI solutions using modern frameworks, optimize ML pipelines, and integrate AI functions into production systems.

In this role you develop Python-based dashboards and applications, prepare data with Pandas, visualize KPIs with Plotly, implement models with scikit-learn, deploy solutions and present results to management.

In this role, you will develop ML models, optimize LLMs, and manage end-to-end pipelines while implementing containerization with Docker and cloud deployments using AWS.

In this role, you will develop software solutions with cutting-edge Machine Learning technologies like ML .NET and TensorFlow, working on innovative .NET and Angular projects as part of a team.

In this role, you develop prototypes and maintain a cloud solution for data storage and processing. You'll collaborate closely with hardware engineers and optimize firmware on test benches and vehicles.

Development and implementation of machine learning models for business applications. Analysis of large amounts of data (structured and unstructured data) for pattern recognition and forecasting. Selection and implementation of suitable algorithms (e.g....