Top Artificial Intelligence Jobs in Munich

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

As an AI Research Engineer focused on AI Safety, you will develop techniques for evaluating AI products, enhance decision-making via uncertainty quantification, and ensure robustness against adversarial attacks.

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.

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

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.

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.

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

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 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.

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.