Top Artificial Intelligence Jobs in Hamburg

The role involves integrating AI tools into .NET and C++ applications, optimizing models for performance, and collaborating with engineers on deployment and monitoring.

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

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Design, build, and maintain end-to-end scalable data pipelines and Snowflake-native warehouses; optimize SQL and performance; implement Azure-based data platform solutions; develop Power BI semantic models; enable AI/ML data workflows; enforce governance, CI/CD, and security; collaborate with stakeholders and mentor engineers.

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.

Build and ship native Android features for an AI-enabled neobank app using Kotlin. Implement clean user flows for financial services, integrate backend APIs, optimize performance and reliability, and apply on-device AI where it improves UX. Collaborate with product and design, use analytics to iterate, and maintain high production quality.

Build and ship native Android features for an AI-powered neobank using Kotlin. Design clean user flows for financial products, integrate backend APIs, improve performance and reliability, use analytics to iterate, and implement on-device AI where it improves UX.

Build and ship native iOS features in Swift for an AI-enabled neobank. Implement clean user journeys for insurance, payments and financial services, integrate backend APIs, optimise performance and reliability, use analytics to iterate, and add AI-assisted mobile experiences where beneficial.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

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.

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.

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

Design and own a governed semantic layer and metrics models; productionize LLM-powered analytics (text-to-SQL, RAG); implement testing, monitoring, and governance for trustworthy AI answers; raise analytics engineering standards and partner with product and leadership to deliver durable data products.

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.

Lead end-to-end product development for an agentic AI platform for drug discovery: prototype LLM/agentic workflows, convert manual scientific workflows into reusable products, evaluate integrations, collaborate with scientists, engineers and customers, and support demos, pre-sales and adoption.

Lead development of an autonomous agentic AI scientist for drug discovery: architect multi-step reasoning agents, bridge AI and wet-lab experiment design, prototype to productionize agentic systems, publish research, and collaborate with biological experts.

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.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

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.

Design, build, and maintain production-grade GenAI systems and Python-based APIs. Implement end-to-end RAG, vector DBs, multi-agent systems, and secure MCP infrastructure. Optimize LLM integrations (OpenAI, Anthropic), event-driven architectures, and real-time messaging. Collaborate cross-functionally, create and refine prompts, and ensure reliability, scalability, and security in production generative AI solutions.

Own and scale Impossible Cloud's global GTM for GPU and AI infrastructure: define segmentation, pricing, and playbooks; build and lead global GTM teams; align product and engineering with market needs; drive partnerships, enterprise deals, and thought leadership to accelerate adoption.

The Principal AI Scientist will architect and implement advanced Generative AI models, train and optimize LLM systems, and collaborate across teams to enhance performance in AI applications.

Looking for a Senior AI Research Scientist to finetune LLMs, create conversational workflows, and innovate methods for faster inference.

As a Pathologist at Mindpeak, you will ensure the medical quality of AI systems, validate annotations, and lead pathology projects for scalable cancer diagnostics.

Develop and maintain backend services for AI-driven digital pathology, collaborating with cross-functional teams on technical solutions and automation tools.