Top Artificial Intelligence Jobs in Munich

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.

The Principal AI Scientist will architect and implement advanced Generative AI models, train and optimize LLM systems, and collaborate across teams to enhance performance in AI applications.

The role involves developing and delivering workshops on AI tools, supporting the adoption of AI across ABB, and managing training on AI concepts and change management.

As a Founding Engineer, you will develop AI solutions with 3D computer vision, optimize networks, and integrate them into real-time systems, alongside experienced founders.

Serve as a senior pre-sales Solutions Architect for Databricks AI/BI product line: drive account strategies, deliver demos/workshops, advise on lakehouse analytics, resolve tier-3 technical issues, and influence product roadmap to increase adoption.

Localize and adapt German-language dubbing using Deepdub's AI tools. Prepare and edit audio/video, adapt scripts, proofread translations/subtitles, and quality-check dubbed performances to preserve emotional intent.

The role involves testing and debugging AI clusters, maintaining hardware, and collaborating with development teams to resolve issues across networking components.

Partner with customers to design, prototype, and scale AI-enhanced developer workflows using OpenAI Codex. Build demos, run workshops, produce technical guidance, gather product feedback, and advise on architecture, safety, and operational readiness to drive adoption.

Own outbound and inbound pipeline for AI cloud users, manage outreach automations, re-engage sign-ups, coordinate discovery and partner calls, maintain CRM hygiene, attend events, and design GTM experiments with founders and CRO.

The Senior Agentic AI Engineer will develop cutting-edge GenAI solutions, design high-performance AI modules, and ensure system integration while leading cross-functional teams.

The Senior Agentic AI Engineer will design and deploy GenAI solutions, integrating intelligent agent services, leading AI research, and enhancing code quality to transform global logistics.

The role involves developing sophisticated LLM-powered autonomous agents, integrating intelligent services, and ensuring systems' scalability and reliability. Responsibilities include architecting AI modules, leading agile sprints, and monitoring production lifecycle with CI/CD roles.

Lead the architectural direction for Generative AI initiatives, establish CI/CD pipelines, mentor engineers, and drive AI experimentation for logistics solutions.

Lead technical initiatives for Generative AI in logistics, design architecture, implement evaluation pipelines, and mentor engineers.

Lead AI transformation initiatives in procurement, creating impactful research, developing strategies, and advising clients on AI integration and analytics for business outcomes.

As a PhD Intern, you'll research and develop methods for adapting LLMs, build multimodal models, explore reinforcement learning, and evaluate user-centric outcomes, collaborating closely with teams to prototype and document findings.

As a PhD Research Intern, you will develop methods for 2D and 3D models, evaluate AI workflows, and collaborate on research projects. You'll produce documentation and potentially publish your findings.

Lead AI initiatives for public sector collaboration, drive business development, maintain sales tracker, mentor teams, and develop market strategies.

The role involves achieving sales targets for AI/ML products, engaging with customers to address their needs, and collaborating with various teams to drive sales success.

The AI Success Engineer engages with customers post-sale to ensure successful AI adoption. Responsibilities include managing account health, leading technical enablement, identifying use cases, and facilitating cross-functional collaboration to deliver measurable business value.

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.