Top Machine Learning Jobs in Munich

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.

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.

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

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

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.

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.

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.

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

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

The Senior Data Engineer designs, maintains, and optimizes ML applications and data pipelines, ensuring compliance and quality while mentoring junior engineers.

As a Senior Data Engineer, you will design and maintain ML applications, manage workflows, build data pipelines, and mentor junior engineers within a global team.