Top Artificial Intelligence Jobs in Hamburg

Manage and grow AI influencer brands by refining identities, optimizing content strategies, and driving performance across social platforms, focusing on audience connection and engagement.

Support and implement global pricing strategy, provide pricing recommendations, lead fee negotiations, perform quantitative analysis and financial modelling, improve pricing processes and reporting (including SAP data entry), oversee pricing research and competitive intelligence, adopt AI/technology for fee modelling, and lead a high-performing pricing team.

Lead a team of Data and AI engineers, develop AI solutions, design cloud infrastructure, and streamline data processes. Collaborate with stakeholders to align AI efforts with business goals.

Advise financial institutions on AI governance and compliance with EU AI Act and GDPR. Conduct model lifecycle risk assessments, design governance and compliance-by-design frameworks, support validation, documentation and audit readiness, and advise senior stakeholders on AI risk mitigation.

As a Marketing AI & Automation Manager, design and implement AI-driven automation use cases, optimize marketing systems, and collaborate across teams to enhance customer journeys.

The AI Support & Knowledge Manager will optimize AI performance, manage support content, design conversation flows, create automations, and oversee AI support KPIs.

The Software Engineer, AI will evaluate, compare, and refactor AI-generated code while providing detailed explanations for decisions. They will engage in asynchronous work to enhance large-language model training.

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

Citrine Informatics invites applicants to submit resumes for general opportunities. They review applications periodically for potential new roles in AI-driven materials and chemicals.

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.

Design and develop intelligent data solutions, optimizing data pipelines and automation systems to enhance Statista's analytics and AI products.

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

Train large-language models (LLMs) by evaluating, ranking, repairing, and refactoring code. Provide detailed feedback and maintain the RLHF pipeline.

The Software Engineer will analyze, rank, and improve AI-generated code, providing feedback for reinforcement learning in a remote role.

The role involves training large-language models to improve code generation, reviewing and editing AI-generated code, and providing feedback for reinforcement learning refinement.

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.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

The role involves managing compliance with AI and e-commerce regulations, handling contracts, keeping compliance documentation, and conducting risk assessments. Regular collaboration with the Ethics and Compliance Officer is essential.

As a Software Engineer, you will help train large-language models in code evaluation and training, focusing on Ruby, with an emphasis on code review and improvement.

Train large-language models to improve code quality by comparing snippets, providing feedback, and refining AI-generated code. Requires strong communication skills and attention to detail.

Responsible for training large-language models by reviewing, ranking, and improving AI-generated code. Requires strong software engineering skills.

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

The AI Automation Engineer engages with customers to understand their needs, leads technical sessions, designs applications on Five9, and manages requirements for cloud implementation.