Top Machine Learning Jobs in Munich

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 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.

The Functional Safety Manager will lead ISO 26262 certification efforts for SoC products, define safety strategy, run risk assessments, and manage safety documentation while collaborating with HW/FW/SW teams.

As a Partner Solutions Architect, you will build and maintain technical relationships with partners, support solution development, and enable AI practices to drive revenue.

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.

Develop and integrate reinforcement learning agents into autonomous aerial systems, ensuring reliability and performance. Collaborate with teams and enhance the software stack while mentoring peers.

Lead the core biometric recognition technology team, managing the full lifecycle of ML systems focused on iris and face recognition while ensuring privacy and reliability at scale.

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.

Lead the LLM team to architect, train, and deploy AI models, optimizing real-time user experiences and creating advanced moderation systems.

The Applied Machine Learning Scientist will innovate and implement ML algorithms to enhance advertising performance, collaborate with engineers, and prototype in data-driven models.

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.

The Senior Technical Product Manager will shape product strategy for Constructor's platform, ensuring capabilities support scalability and security for learning applications.

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.