Top Machine Learning Jobs in Cologne

The role involves developing AI solutions for automotive applications, focusing on machine learning techniques for perception, planning, and prediction tasks.

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.

The Data Scientist will solve real-world problems utilizing data science techniques and build end-to-end data pipelines, collaborating with multiple teams to deliver solutions.

Lead the development of robot policies and task planning. Collaborate with cross-functional teams to create real-world robotics solutions, incorporating AI technologies and MLOps practices.

Lead the development of high-fidelity simulations and validation workflows for robotic systems, focusing on sensor simulation and mechanical modeling to ensure reliable performance in real-world and virtual environments.

Intern will explore collaborative learning and differential privacy while developing efficient systems for large ML models, aiming for academic publication.

The intern will contribute to MLOps, design AI/ML systems, implement research ideas, and work on various optimization models, while gaining hands-on experience.

Lead the development of fraud prevention products, collaborating with technology and risk teams, analyzing trends, and ensuring compliance with regulations.

The AI Researcher/Engineer will develop AI agents to autonomously conduct scientific discovery, leveraging AI systems and scientific computing in materials research.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

As an Applied ML Engineer, you will build and scale data pipelines for video generation, ensuring data quality and optimizing preprocessing workflows.

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.

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.

Lead and grow an ML engineering team to build, operate, and maintain production-grade ML systems (recommenders, search). Define quality standards, collaborate with product and data teams, and remain hands-on to guide architecture and delivery for business impact.

Develop and maintain AI and ML algorithms, create data pipelines, collaborate with cross-functional teams, and implement solutions for business requirements.

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

Lead the Voice team at Rasa, focusing on mentoring engineers, driving processes, and delivering voice features while maintaining strong communication and async practices.

This role involves enhancing a product through computer vision and deep learning, driving document parsing, improving quality metrics, and mentoring team members.

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.