MLflow Jobs in Germany

In this role, you will develop generative AI systems, design and optimize models like LLMs and Diffusion Models, and integrate data-driven architectures into production environments.

In this role, you take ownership of evolving our AWS and Hetzner infrastructure, operate stable environments, foster containerization and CI/CD tools, and ensure security and compliance.

In this role, you will develop complex machine learning models and backtesting frameworks to analyze real-time esports data. You will enhance model performance and implement them into production-grade pipelines.

In this role, you will develop advanced computer vision models, implement them on cloud and edge environments, and enhance data pipelines for real-time analysis and model recognition in various applications.

In this role, you will work on integrating and maintaining a cloud-native MLOps platform, configure Kubernetes environments, and automate workflows using infrastructure-as-code and CI/CD.

In this role, you will build LLM platforms and on-prem GPU clusters, monitor performance, and scale hybrid architectures while collaborating closely with data scientists and developers for optimal AI solutions.

In this role, you will develop modern data products on our Azure Databricks platform, manage a data domain, and be responsible for integrating new data sources and modeling business logic.

In this role, you shape our data platform, develop data products for various business areas, and automate data pipelines on Azure Databricks while collaborating closely with the departments.

In this role, you will develop modern data products on the Azure Databricks platform, manage data pipelines, ensure data quality, and work closely with business departments.

In this role, you will develop modern data products and actively shape our data platform on Azure Databricks by creating data pipelines, ensuring quality, and closely collaborating with business departments.

In this role, you will design data processing pipelines, maintain existing data infrastructure, and collaborate closely with data scientists to optimize ML models and develop CI/CD pipelines.

In this role, you build the infrastructure for distributed training, deployment, and experimentation, utilizing technologies like Kubernetes and PyTorch to efficiently transition ML models into production.

In this role, you will develop scalable microservices using Java and Spring Boot, integrate external systems, and manage CI/CD pipelines for automating AI workflows in cloud environments.

In this role, you will develop scalable data pipelines and optimize data models for analytics and AI applications while collaborating closely with various functional areas.

In this role, you will develop advanced computer vision models for medical image analysis, monitor production models, and integrate ML pipelines into product workflows using modern tools and frameworks.