Top Machine Learning Jobs in Munich

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.

Seeking a Senior/Lead Machine Learning Engineer with expertise in inference optimization, model acceleration, and high-performance systems for developing real-time multimodal models.

As a Machine Learning Engineer, you'll develop machine learning solutions for medical data analysis, particularly focusing on surgical video processing. You will engage in all phases of the ML development lifecycle to enhance surgical procedures through intelligent software components.

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.

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.

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.

Internship focused on enhancing ML/LLMOps and AI agent infrastructure within AWS: evaluating LLM frameworks, building RAG pipelines, automating model evaluation/deployment, documenting findings, and contributing to ML/data pipelines.

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.

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.

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.

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.