Top Artificial Intelligence Jobs in Berlin

As Head of Product, you will shape the product organization, own the roadmap, scale the team, and ensure customer satisfaction through optimized processes and product quality.

The Director of Data & AI will develop a product strategy for Upvest's data, oversee AI product development, and lead a high-performing team in a regulated fintech environment.

Lead and execute the company-wide AI roadmap, enable teams to use AI tools, identify and prioritize AI initiatives across the value chain, advise executive leadership, grow the AI Champions network, ensure governance/security/compliance, and scale AI opportunities organization-wide.

Lead go-to-market planning for JetBrains AI Ecosystem launches, create clear messaging and launch assets, coordinate stakeholders, scale campaigns, gather market and customer insights, and track campaign performance to improve processes.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Design, build, and scale production AI workflows and agents that automate operational processes. Identify high-value automation opportunities, prototype and productionize LLM/RAG-based solutions, maintain prompts/templates, set up AI toolchain, implement security and monitoring, and enable teams through training and operational guidelines. Measure impact via hours saved, error reduction, and throughput improvements.

Post-sales technical lead for strategic EMEA accounts, advising on cloud-native and AI deployments. Own technical relationships, troubleshoot escalations, design architectures for LLM/agentic workloads, drive product adoption, deliver training, and feed customer insights to Product and Engineering.

As Head of Product - AI, you will define AI as the core of our platform, lead product managers, and shape the user experience for buyers and sellers.

As a Senior Machine Learning Engineer, you will develop and scale customer-facing AI models, ensuring quality integration with business solutions, and mentoring peers.

Own global go-to-market strategy and positioning for SUSE's AI portfolio. Translate technical cloud-native, containerized, and edge inferencing capabilities into executive-level messaging, create high-value content, enable sales and partners, lead ecosystem marketing, and provide market and competitive intelligence to influence product and GTM decisions.

Lead product analysis and delivery for AI-powered digital products: translate business needs into user stories, shape AI use cases, run A/B tests, manage end-to-end delivery, lead agile ceremonies, coordinate stakeholders, and drive continuous improvement.

The AI-First Graphic Designer will create visual assets for digital platforms, maintain brand consistency, and collaborate on marketing campaigns. The role requires managing multiple design requests in a fast-paced environment.

The Senior HPC and AI Network Software Architect will develop scalable AI systems focused on distributed training and inference, collaborating on software and hardware integration to enhance performance.

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 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 Operations Specialist will lead AI initiatives, optimize operations, manage projects, and drive business strategies to improve efficiency and user acquisition.

As a Creative Gen AI Specialist, you'll build efficient automated workflows, produce high-performance ads, and integrate AI models while collaborating closely with creative teams and data scientists to optimize assets based on real-time performance data.

The Senior Backend Engineer will architect and maintain backend services, integrating AI-powered support systems while ensuring reliability and performance monitoring. Responsibilities include end-to-end feature ownership and mentoring team members.

The Senior Full Stack Engineer will design and build backend and frontend systems for an AI Investigation Agent, ensuring reliable performance and collaborating closely with teams to shape product features.

Develop computer vision models for object recognition and video understanding while evaluating and improving their performance for real-world applications.

Design and integrate AI capabilities into SAP-based enterprise applications, build and scale prototypes into production using ABAP Cloud on SAP BTP, integrate LLMs with orchestration tools (LangChain/LangGraph), apply RAG approaches for enterprise solutions, and collaborate with customers on claims-management transformation.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

As a Senior Sales Engineer, you will work closely with the sales team to deliver technical support, create demonstrations, and recommend solutions for clients using NiCE technologies in the DACH and France region.

Lead presales for complex enterprise deals across DACH and expansion markets: run discovery and technical deep dives, design tailored AI Agent solutions, deliver demos and POCs, represent the company at events, and feed customer requirements back into product and enablement.

Design and build agentic conversational systems combining LLMs, reasoning components, and data pipelines. Lead ML/NLP model training, evaluation, optimization, deployment, and experimentation. Integrate intelligent agents into recruiting workflows, mentor engineers, and improve reliability, personalization, and observability of production ML systems.