Top Artificial Intelligence Jobs in Cologne

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

Develop and maintain open-source, silicon-optimized AI/ML inference application packages (Inference Snaps) for Linux/Ubuntu Core. Debug, write high-quality code, review upstream contributions, secure and optimize local inference deployments across embedded devices to gateways, and collaborate with a distributed team and stakeholders.

Customer-facing ML/GenAI engineer who advises customers, runs demos and strategic reviews, drives product adoption, partners with sales and engineering, and helps expand accounts by implementing best practices for production ML/LLM systems.

Partner with EMEA AI/ML teams to drive adoption of Arize's observability platform, manage accounts through onboarding and renewals, run workshops/QBRs, identify upsell opportunities, and coordinate technical resources to ensure customers achieve measurable AI outcomes.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

Design and implement user-facing features from concept through implementation, combining UX design and front-end engineering. Build, iterate, and maintain UI/UX and business logic to drive engagement and conversion, collaborate with product/marketing/support, participate in code reviews, and leverage modern tools and deployment workflows.

Design and implement next-generation AI-powered features for JetBrains IDEs: integrate and enhance AI agents, build novel IDE capabilities, evaluate performance and reliability, and own end-to-end feature delivery.

Design and implement AI-powered UI features for JetBrains IDEs using Compose Multiplatform and Swing. Collaborate with designers, improve UI architecture and component reuse, ensure responsiveness and performance in complex desktop applications, and contribute to UI testing and developer tooling features.

Lead design and implementation of AI-native features for PyCharm and Python tooling. Architect integrations (MCP, agents), prototype and ship features, guide engineering decisions, evaluate AI tools/providers, and expose IntelliJ Platform capabilities to AI workflows while collaborating with product, ML, QA, and senior developers.

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.

Designs and implements AI, automation, and analytics solutions for supply chain. Develops data models, governance, reporting, and advanced analytics; collaborates with process owners to enable data-driven decisions and trains/supports business users.

Lead deployment and scaling of AI/ML models, agentic tools, and automation across R&D. Drive MLOps, platform integration, compliance, stakeholder partnerships, capability building, end-user support, and metrics tracking to deliver measurable value.

Produce narrative-driven long-form AI-generated videos end-to-end: concept, prompting, generation, editing, compositing, motion graphics, color correction, and maintaining character/style continuity using emerging AI video tools.

Join the Compliance team to own AI and e-commerce legal workflows: GDPR and data protection documentation, AI systems inventory, risk assessments, product/feature reviews, contract and IP issue handling, TOS/privacy updates, and monitoring legal developments. Work with the Ethics & Compliance Officer and review uncensored AI content as needed.

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.

Manage the GTM AI Engineering team overseeing automation, AI agent strategy, and integration with sales and marketing for revenue growth.

As a Senior Forward Deployed Engineer, you'll deliver AI solutions, engage with customers, and lead project lifecycles, including deployment and integration.

Looking for a Mid/Senior AI Cinematic Video Editor to create narrative-driven video content using AI tools, managing the entire production process from concept to final delivery.

The Senior GTM Engineer at Xentral will develop AI-driven workflows, ensure efficient data flows, integrate marketing tools, and create feedback loops to enhance marketing processes.

The Senior Developer Relations Manager will drive AI technology adoption by engaging with ISVs and enterprise leaders, provide technical leadership in AI and computer vision, and lead thought leadership discussions for NVIDIA's AI ecosystems.

Lead the design and deployment of AI and automation solutions, focusing on scalable applications, automation of workflows, and integration of LLMs in operational processes.

The AI Engineer will develop and maintain AI infrastructure, implement ML solutions, curate datasets, and collaborate with teams to enhance products.

The AI Engineering Intern will design, test, and deploy scalable AI systems, integrate models, and work on inference optimization, collaborating with data scientists on complex problems.