Top Machine Learning Jobs in Munich

The role involves designing and testing AI solutions, managing research projects, collaborating with teams, and introducing new ML concepts for product development.

The AI Content Evaluator will review and assess content for alignment with guidelines, ensuring quality and consistency in annotation. Responsibilities include evaluating various content types, applying structured criteria, and adhering to project guidelines.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The Pricing Advisory professional will assist clients in enhancing pricing strategies through consultation, model development, implementation support, and training sessions, while managing stakeholder relationships and navigating challenges in pricing sophistication.

Lead technical delivery with OpenAI partners across EMEA to design, deploy, and scale production-grade AI solutions. Provide hands-on prototyping, integration, architectural guidance, and governance while collaborating with partner teams and internal stakeholders to ensure reliability, security, and repeatable deployment patterns.

Lead developer-facing work on advanced real-time rendering and neural graphics: optimize GPU/CPU performance, develop and tune neural rendering and AI models, collaborate with AAA studios and NVIDIA architecture/driver teams, build demos, publish and present research.

As a Senior Forward Deployed Engineer, you'll deliver AI solutions, engage with customers, and lead project lifecycles, including deployment and integration.

The Senior Product Manager will own and drive the development of Kraken's Algorithmic Execution & Strategy Engine, focusing on execution algorithms, API specifications, and client engagement to optimize trading strategies.

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

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.

As Lead Systems Engineer, oversee integration of EO/IR sensing systems, manage technical suppliers, define requirements and ensure operational readiness.

The Senior AI Engineer will design and develop intelligent conversational systems for recruiting, focusing on agentic workflows, ML/NLP products, and system integration.

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.

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.

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.