Top Artificial Intelligence Jobs in Germany

Assess and evaluate AI-generated technical content, craft and answer advanced ML/AI questions, identify errors and hallucinations, rank responses by correctness and clarity, and provide precise feedback to improve model performance.

Lead EMEAI Logistics operations, managing a team of 140+ logistics professionals to meet customer expectations and drive digital transformation. Develop logistics strategies to improve service and reduce costs while ensuring compliance with performance standards.

Lead design, development, testing, and maintenance of software products. Drive technical architecture, collaborate with Product, Engineering, and QA, optimize performance, build APIs and integrations, and apply AI tools to improve development efficiency and quality within Agile processes.

Lead design and delivery of scalable AI solution architectures, own end-to-end AI projects from concept to production, implement MLOps and CI/CD, monitor and optimize performance, manage and mentor an AI/data science team, and collaborate with AI leadership and business units.

Lead discovery, definition, and delivery of AI-powered B2B SaaS features. Research auditors' needs, prototype with LLMs/agents, collaborate with engineering/design, run customer interviews, write PRDs, and iterate to ship reliable audit-quality products.

Hands-on platform engineering role building and operating an internal Agentic AI platform: implement infrastructure-as-code, security and secrets management, GitOps delivery, observability, autoscaling, API/AI gateway routing, and run day-to-day operations including incident response, backups, and runbooks.

Lead engineering enablement across eight companies to cascade CTO AI vision into team discipline. Detect and package successful practices, run cross-company diffusion, operate cadence of validation and demos, measure adoption and outcomes, triage deeper needs to PoCs/workshops, and capture reusable artifacts and metrics.

Design, build, and operate the AI storage layer for GPU-heavy edge and core deployments. Architect and optimize storage for distributed training and inference, integrate storage with Kubernetes (CSI), tune performance (RDMA, NVMe-oF, GPU Direct Storage), lead reliability and operational practices, and provide staff-level architectural ownership and cross-team influence while executing hands-on storage engineering.

Own design, deployment, and operation of high-performance AI GPU fabrics and datacenter networking (RoCE, RDMA, BGP/ECMP, EVPN/VXLAN). Provide staff-level architecture, cross-team technical leadership, incident escalation, automation (Python/Bash), and operational standards for global datacenter and edge deployments, including inter-datacenter transport and security.

Own customer deployments of ProcessOS: deploy and configure Camunda clusters, build custom agents and connectors, debug integrations, drive adoption, document playbooks, feed product improvements from field work, and hand off operating capability to customers.

Deploy and validate ProcessOS at enterprise customers: configure Camunda clusters, integrate legacy systems, build custom agents and connectors, measure/improve deployed workflows, document best practices, and hand off operational capability while feeding product improvements back to engineering.

As an AI Operations Intern, you will support onboarding, manage customer journeys, enhance internal processes, and collaborate with teams to improve AI products.

Operate and support large-scale AI infrastructure across datacenters: monitor production GPU-backed Kubernetes platforms, troubleshoot hardware, networking and platform incidents, participate in incident response and RCA, improve observability and automation, and maintain operational runbooks.

Lead technical operations for large-scale AI GPU infrastructure and Kubernetes platforms. Investigate and resolve complex incidents across networking, storage, hardware and Linux; drive reliability, observability, capacity planning, automation, and root-cause remediation. Provide technical leadership, mentor engineers, develop runbooks and operational standards, and collaborate with engineering, vendors, and datacenter teams to improve platform resilience and adopt AI-powered operational capabilities.

Build and operate production-grade AI systems (RAG and agentic) on sensitive enterprise data: design retrieval pipelines, embeddings, vector search, evaluate retrieval quality, prototype in Python and implement production gRPC services in Go, select AI tooling, and ship AI features and internal automation with observability and safety in mind.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

As a founding product hire, you'll define the product vision, create user journeys, maintain the product backlog, and conduct user research for a cybersecurity platform.

The role involves sourcing and evaluating AI infrastructure founders, supporting them through early stages of investment, and representing the firm with technical expertise.

Lead public affairs strategy in Germany and the EU, engaging with government and regulators on AI, semiconductors, and computing policies. Build relationships, represent the company in policy forums, and develop narratives for public communications.

As a Machine Learning Engineer, you'll develop and improve ML models for geospatial analytics, collaborating with various teams to enhance performance and reliability of ML systems.

As an AI Engineer, you'll design AI services, build NLP and LLM applications, and optimize performance for a global SaaS platform.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

As an R&D Engineer, you will design and optimize AI pipelines, integrate LLMs into testing workflows, and analyze semiconductor data.

The Chief of Staff will support the CEO in executing company strategy, managing financial operations, applying AI to improve processes, and leading high-impact projects across the organization.

The Senior Software Engineer will focus on Machine Learning model development, data management, model deployment, and staying updated on NLP advancements.