Top Artificial Intelligence Jobs in Berlin

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 and iterate UX/UI for an AI-powered OS used by renewable installers. Own end-to-end product design, prototype quickly, improve flows, collaborate with product and engineering, and use data and research to drive adoption.

Build and scale AI-driven automation solutions using LLMs and agent frameworks. Design multi-step workflows, integrate AI with internal systems (HR, finance, legal, ticketing), automate document processing and data extraction, and train internal teams. Collaborate with technical leads, product, and IT to deliver practical, production-ready automation and iterate quickly.

Design, build, and maintain ELT pipelines and dbt SQL models for analytics; optimize performance, scalability, and costs; apply AI-enabled tools to improve engineering workflows; collaborate to translate requirements into production-grade data assets.

The role requires working closely with customers to design AI-powered solutions, translating business problems into technical plans, and leading solution implementation.

The role involves developing new AI model architectures and adapting existing models, conducting experiments, and contributing to technical strategy in a high-growth research environment.

Build and maintain agentic, AI-powered frontend features across Scalable's products. Work in a cross-functional Data Science & AI team to design, implement, and ship components (CLI, MCP server, agentic chat), lead technical discussions, make architecture decisions, and ensure code quality, security, testability, and scalability.

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.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The role involves evaluating AI outputs, correcting texts, analyzing multimedia, and providing culturally relevant content while adhering to guidelines.

As an AI Process Forward Deployed Engineer, you will deploy enterprise workflows, improve systems, drive adoption, and collaborate across teams to enhance AI integration in business processes.

Lead end-to-end organic growth programs for B2B tech clients, owning strategy, execution, deliverable quality, renewals, and commercial-impact metrics across a portfolio of up to ten accounts. Prioritize work, set and keep commitments, evaluate recommendations, and partner with a production team that executes briefs, decks, and data.

Lead deployment, debugging, benchmarking, and performance optimization of large-scale GPU training and inference workloads. Work with NVIDIA teams and external customers to diagnose cluster bottlenecks, improve efficiency, guide scaling strategies, and contribute to resiliency for Europe's Sovereign AI initiatives.

Build full-stack, user-facing AI applications for public procurement: design, implement, and deploy features using the company tech stack, integrate LLMs, own features end-to-end, improve reliability, and collaborate closely with founders and users.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

As a Senior React Engineer, you'll develop AI products using React and Python, create high-performance frontends, integrate AI services, and ensure system reliability from MVP to production, while having creative freedom.

As a Principal Forward Deployed Engineer, you'll deploy JetBrains Central in enterprise environments, implement AI governance, mentor teams, and advise customers on AI-native development best practices.

Build production-grade AI agents, LLM apps, RAG systems and automations for fintech workflows (onboarding, KYC, support, risk, CRM). Work with product and engineering to ship, evaluate, and improve reliable, secure, cost-effective AI-enabled systems that replace manual processes.

Lead EMEA go-to-market for Physical AI by sourcing executive-level pipeline, accelerating top accounts, building EMEA-specific playbooks, enabling regional sales, and converting lighthouse wins into sustained cloud consumption across robotics, autonomy, simulation, and related AI-native industries.

Design rigorous, deterministic advanced physics problems and provide complete verified solutions for AI training and evaluation. Create reproducible simulations or computational workflows (using Python and scientific libraries), document reasoning clearly, and ensure technical precision. Contribute to problem design that tests deep multi-step physical reasoning.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

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.

Author and refine a systems-engineering curriculum for experienced engineers: shape syllabus, define learning objectives, produce and fact-check lessons using AI tools, design hands-on projects and rubrics, and iterate with LX designers to meet milestone deliverables over a 4–6 month, ~15–20 hr/week engagement.