Top Artificial Intelligence Jobs in Hamburg

The intern will contribute to MLOps, design AI/ML systems, implement research ideas, and work on various optimization models, while gaining hands-on experience.

The People Operations AI & Analytics Partner will enhance People processes using analytics, automation, and AI, working closely with various teams to optimize workflows and maintain compliance.

Provide hands-on deployment, debugging, benchmarking, and optimization of large-scale AI training and inference workloads on NVIDIA GPU clusters. Work with customers and internal teams to identify bottlenecks, improve efficiency, and scale workloads reliably while contributing to resilience features for sovereign AI initiatives across Europe.

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

Join the math libraries team focusing on high-performance numerical software for AI and HPC. Collaborate with engineers and manage technical roadmaps while optimizing algorithms for GPU performance.

The role involves advising on AI and privacy legal issues, supporting product teams, managing compliance, and guiding enterprise customers and internal teams on privacy legislation.

The AI Researcher/Engineer will develop AI agents to autonomously conduct scientific discovery, leveraging AI systems and scientific computing in materials research.

The role involves adapting scripts for dubbing, reviewing translations, evaluating voice performance, and efficiently managing multiple productions based on client demand.

The Senior Infrastructure Engineer will design and maintain AWS infrastructure for AI/ML workloads, focusing on deployment, security, and collaboration with ML teams.

Lead the LLM team, architect systems, oversee model lifecycle, and develop advanced moderation strategies for high-traffic generative AI applications.

The Senior Product Manager will own the strategic roadmap, lead market research, manage monetization strategies, and mentor product managers within an AI and EdTech environment.

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

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

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 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 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 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.

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.