Top Artificial Intelligence Jobs in Berlin

Work with senior engineers to build AI tooling and integrations using agentic coding tools, create proof-of-concept apps on Xsolla APIs/SDKs, ship production-facing code, and present weekly demos. Focus on fast, autonomous development and collaboration within a global intern cohort.

Lead and coordinate technical AI/ML programs bridging research and lab implementation. Plan and deliver projects, manage compute/resources/dependencies, liaise with industry and academic partners, drive proposals and pilots, refine scalable processes, track metrics, and support IP, compliance, and publication efforts.

Own end-to-end development of AI-powered product features: design prompts, tools, memory and agent workflows; deploy and stabilize LLMs in production; optimize latency, cost, and reliability; build evaluation frameworks; debug model, orchestration, infra, and UX issues; and collaborate with product and engineering to deliver measurable improvements.

Build end-to-end AI-native product features across frontend, backend, and AI integrations. Design and deploy reliable agent workflows, integrate LLMs/memory/tools, optimize streaming low-latency interactions, improve observability, fallback and recovery mechanisms, and iterate on production failures to increase reliability of multi-step workflows.

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.

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.

Own and translate SAP consulting knowledge into AI agent workflows; design scalable architectures for SAP landscapes (S/4HANA, ECC); collaborate with enterprise clients during onboarding and rollouts; partner with AI and engineering teams to ensure technical accuracy; build reusable reference architectures and act as domain expert embedding SAP knowledge into the product.

Build and maintain end-to-end AI product features using LLM APIs, including chat UX and backend integrations. Design RAG and retrieval pipelines, agent orchestration, evaluation infrastructure, and scalable FastAPI/Python backends while ensuring security, privacy, and operational monitoring. Collaborate with Product, Legal Engineering, and Design to prototype and ship AI-powered legal workflows.

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

Own and evolve production voice AI systems across telephony, speech, and LLM stacks. Build, ship, and scale phone agents; implement observability, evaluation, and tooling; collaborate cross-functionally to integrate voice AI into product workflows.

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.

Lead end-to-end architecture for enterprise data, analytics, and AI in a Microsoft-first environment. Translate business needs into secure, scalable designs, prototype and guide delivery teams, ensure governance, security, and production readiness, and enable enterprise AI (Azure OpenAI, RAG) and BI (Power BI) solutions.

Lead rapid end-to-end prototyping of LLM-powered agent systems: build working prototypes, design experiments measuring quality/latency/cost/user impact, validate with users, produce reference implementations, and hand off to product teams to inform roadmap decisions.

Lead enterprise growth across top European law firms and corporate legal departments, manage retention and expansion through a team of Retention Managers, oversee digital revenue and e-commerce channels, coach cross-border account executives, negotiate high-value enterprise agreements, and present commercial strategy to executive leadership.

The AI Search Associate will onboard clients, advise on SEO strategies, and sell AI search products, ensuring client success in AI-driven search.

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.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

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.

Create short- and long-form AI-generated educational and entertainment content for Instagram, TikTok, and YouTube. Rapidly test content hypotheses, analyze performance, research trends and competitors, and iterate on hooks, storytelling, and editing. Collaborate with the product team and continually experiment with AI image/video generation and editing tools.

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 AI Research Engineer will research and develop novel model architectures, adapt open-source models, and contribute to the technical strategy and culture of the team.