Top Machine Learning Jobs in Germany

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.

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.

Design and implement scalable machine learning systems, collaborate with product teams, and apply MLOps best practices in production environments.

As a Senior ML Researcher at JetBrains, you will train LLMs for software engineering agents, design experiments, and mentor junior colleagues.

The Senior Machine Learning Engineer will design evaluation frameworks, diagnose model performance, develop ML systems, and mentor junior engineers while collaborating across teams.

Design and maintain MLOps infrastructure, productionize research code into Python/C++ packages, implement CI/CD and IaC (Terraform/Ansible) across Cloud/Edge/On‑prem, enforce engineering standards (Git, Docker, testing), add observability (MLflow, ELK), and consult scientists to optimize workflows and deployments.

As a Senior Machine Learning Platform Engineer, you will design and manage data and ML pipelines, implement CI/CD, and optimize cloud infrastructure, focusing on natural language processing.

Design, build, and scale core infrastructure for machine learning models, manage production systems, and implement best practices in MLOps.

The role involves designing and implementing machine learning capabilities for autonomous vehicles, focusing on perception, prediction, and planning systems. Engineers will work on software development processes from model creation to deployment, leveraging established products.

Design and develop AI/ML infrastructure for enterprise software, ensuring reliable deployment and optimization of models in production. Collaborate on architecture evolution and build scalable data pipelines.

The intern will focus on architecting systems for reliable task execution in machine learning agents, implementing verification layers, and optimizing performance.