Top Machine Learning Jobs in Germany

Design, build, and deploy production-grade ML systems and data pipelines in Databricks. Perform EDA, statistical A/B testing, feature engineering, and predictive modeling. Define metrics with stakeholders, produce dashboards and visualizations, and collaborate with product and engineering to drive KPI improvements while applying software engineering best practices.

Develop and scale neural networks for source code tasks, create and improve methods for code generation, editing, and agent-based workflows, mentor colleagues, and produce publishable ML research results.

The Senior AI Engineer will design scalable AI systems, focusing on LLM-powered agents and automation, optimizing delivery operations globally.

The AI / Machine Learning Researcher will conduct applied research, develop prototypes, and work with data to create AI-driven features related to home design.

Lead and mentor a team of Applied Scientists and AI/ML Engineers to design and deliver production-grade AI solutions across structured CRM and unstructured data. Drive technical strategy for agentic workflows, RAG/vector DB systems, and real-time reasoning. Partner with AI Platform on LLMOps and cloud infrastructure, act as a technical authority, and contribute as a high-impact individual contributor to ship customer-focused AI products.

Build and own end-to-end frontend and backend ML platform features, collaborate with product and research to productionize model and agent capabilities, and design scalable, reliable, and secure data science tools.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

This internship focuses on designing solutions for secure data preparation in ML workflows, ensuring data privacy while maintaining model performance. Interns will prototype methods using advanced technologies like Trusted Execution Environments and contribute to academic publications.

Design and scale predictive ML systems for VIS.X, taking end-to-end ownership of various high-impact ML initiatives and shaping the ML architecture.

The Applied AI Engineer will onboard clients on Mistral AI products, manage complex integrations, and drive technological transformations through collaboration with stakeholders.

Lead the development of AI/ML systems for real-time applications, mentor teams, optimize performance, and contribute to the AI/ML community.

The Senior Infrastructure Engineer will design and maintain AWS infrastructure for AI/ML workloads, focusing on deployment, security, and collaboration with ML teams.

The ML/AI Engineer will benchmark GPU platforms for AI workloads, analyze GPU performance, optimize ML workloads, and develop performance visualization tools.

As a Senior AI/ML Engineer at SumUp, you will develop and deploy AI-driven solutions, manage ML infrastructure, and collaborate across teams to enhance customer experience and automate support services.

As a Machine Learning Researcher, collaborate with scientists and engineers to apply ML techniques in stellarator design, integrating solutions from prototyping to deployment, and establishing best practices for the field.

The Machine Learning Engineer will develop high-performance algorithms for retail decision-making, optimizing solutions and supporting data scientists in applying these algorithms effectively.

As an AI Research Engineer at Helsing, you'll architect and enhance deep learning frameworks, optimize infrastructure for distributed training, and develop strategies for large datasets while collaborating with a cross-functional team.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Design, train, evaluate, and optimize machine learning models for document intelligence and GenAI. Collaborate across teams to develop AI systems for document understanding and automation.

Lead the development of robot policies, focusing on task planning, computer vision, and decision-making in robotics. Mentor teams, drive technical roadmaps, and collaborate on scalable AI solutions.

The Senior Robotics AI/ML Engineer at Analog Devices will develop AI-based robot policies, work on task planning and computer vision, and integrate AI into robotics systems, while collaborating with multidisciplinary teams.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.