Top Artificial Intelligence Jobs in Munich

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.

As an AI Engineer in the FDE team, you will develop innovative GenAI solutions, lead production rollouts, and serve as a technical advisor while collaborating across teams.

Lead the technical delivery of custom AI agent solutions for enterprise clients, overseeing project management, stakeholder communication, and technical discussions, while ensuring successful deployment and compliance.

The role involves engineering, testing, and the development of advanced frontend components for an AI-driven cybersecurity product, integrating AI features and ensuring best practices are followed.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

The Fullstack Engineer will focus on product software engineering, agents framework engineering, and R&D in AI and cybersecurity. Responsibilities include hands-on engineering, testing, and integrating AI Agents into existing systems.

The role involves building, deploying, and maintaining AI models, designing evaluation methodologies, and integrating AI into products. It requires strong implementation focus in various AI domains.

As Product Manager for the AI Platform, you'll define and scale AI capabilities, lead strategy, implement use cases, ensure compliance, and collaborate with cross-functional teams to enhance client experiences and operational efficiency.

As an Account Executive, you will drive revenue growth by managing the sales cycle, engaging decision-makers, and negotiating multi-year SaaS agreements.

As an AI Research Engineer, you will develop signal processing solutions, collaborate across teams, and apply AI in real-world scenarios within defence.

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.

Design and implement AI solutions in a collaborative team environment while documenting processes and presenting findings to stakeholders.

As a Data & AI Consultant, you will drive the business through project proposals, tech implementations, and client consulting while supporting team development and acting as a thought leader in the field.

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.

You will design, train, and deploy agents in multi-agent environments, enhancing our reinforcement learning capabilities and integrating cutting-edge AI into production systems.

Lead company-wide AI and automation adoption: run internal programs (hackathons, enablement, dogfooding), conduct AI market watch, produce guidance and content, evangelize successes, and manage and scale the Automation team while overseeing cross-functional delivery and OKRs.

As an AI-Native Content Strategist, you'll create automated content pipelines, identify trends for immediate content production, and engage directly with the CEO to maximize content impact across multiple platforms.

As the AI Agents Solutions Architect at Kraken, you'll design and build an AI-native finance operating system, automating finance operations and ensuring compliance in a regulated environment.

The Principal AI Scientist will develop customized LLM solutions, enhance existing models, and incorporate new AI techniques. Required to collaborate with teams and optimize performance for generative AI applications.

Embed with strategic customers to build production applications using Claude/LLMs, deliver deployment artifacts (MCP servers, sub-agents, agent skills), provide white-glove support, identify repeatable patterns, and travel frequently to drive enterprise AI adoption while ensuring safety and reliability.

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

The Ecosystem Growth Manager will drive the onboarding of GPU providers, AI builders, and strategic enterprise partnerships to enhance the AIVM ecosystem, addressing Web3 challenges and establishing a decentralized infrastructure.

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

The role prioritizes driving Data & AI projects, developing tailored offerings, managing implementations, and supporting talent development as a thought leader in the field.

Lead technical strategy and delivery of AI solutions, managing teams of Applied AI Engineers and directly coding critical project components.