Top Artificial Intelligence Jobs in Berlin

Lead AI initiatives for Data Intelligence product, managing the product lifecycle and collaborating across teams to deliver AI solutions.

The AI Engineer will develop GenAI applications, serve as a technical advisor, and collaborate with teams to influence product initiatives.

The role involves developing data strategies, advising organizations on data management, designing data solutions using cloud services, and conducting workshops with stakeholders.

As a Product Manager, you'll lead Lower's AI initiatives, shaping user experiences, collaborating across teams, driving delivery, and iterating based on performance data and user insights.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

This role involves architecting and building AI agent systems, developing full-stack features, and shaping the technical direction of an early-stage startup's AI platform.

The role involves managing the Autopilot AI product, defining its roadmap, setting metrics, and collaborating with engineering to improve product features. Requires strong communication and relationship-building with cross-functional teams in a B2B SaaS environment.

The Senior Product Owner will define the vision for Better Planner, translate workflows into product requirements, collaborate with engineering, and drive AI-driven innovation in logistics.

As an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

The Marketing Innovation Director will lead AI-driven marketing strategies, pilot new tools, evaluate ROI, and enable cross-functional collaboration to enhance marketing efficiency and effectiveness.

The Senior AI Product Manager will define product vision, lead cross-functional teams, manage product lifecycle, and ensure market delivery, focusing on AI solutions in the B2B SaaS sector.

The AI Data Specialist will perform data-related tasks such as data collection, evaluation, annotation, and object tagging. Must have advanced English proficiency.

Own strategy and roadmap for Nelly's Billing Agent, leading product lifecycle from discovery to launch and ensuring high-quality AI experiences. Drive impact through market understanding and collaboration with engineering and design teams.

Lead the development of LLM-powered solutions, ensuring scalability and security. Oversee AI system integration and collaboration with various teams.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

The AI Engineer will implement and optimize cloud workloads, develop scalable applications, automate AI environments, ensure quality standards, and collaborate with teams on customer projects. Occasional travel is required.

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

WunderGraph seeks a Staff FullStack AI Engineer to lead architecture for AI-driven projects, mentoring engineers and ensuring scalable, secure systems. Responsibilities include backend and frontend development with a focus on AI workflows and enterprise readiness.

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

Drive revenue growth and expand Kaltura's presence in AI solutions for designated verticals. Manage sales cycles, develop GTM strategies, and collaborate across teams to enhance market penetration.

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

Lead a team of researchers to develop advanced AI systems, focusing on multimodal models and engaging user experiences. Responsibilities include mentoring, driving research direction, and collaborating with engineering to deploy innovative features.

Applied AI Engineers will define and deliver AI systems for clients, shape AI visions, build products, and advance the core product using real-world data.

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.