Generative AI Engineer
Design, train, and deploy state-of-the-art generative models and scalable ML pipelines. Collaborate with frontend developers to integrate AI models into production-ready user-facing applications.
155 AI Engineer jobs in Germany available for remote work from home. Apply for positions such as Generative AI Engineer, Senior Generative AI Engineer, Field Application Engineer - AI Software & Hardware and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, train, and deploy state-of-the-art generative models and scalable ML pipelines. Collaborate with frontend developers to integrate AI models into production-ready user-facing applications.
Design, train, and deploy state-of-the-art generative models and scalable ML pipelines. Collaborate with frontend developers to integrate AI solutions into production-ready user-facing products.
Collaborate with sales teams and enterprise customers to drive the adoption of AI products and solutions. Provide technical guidance through meetings and workshops while feeding customer insights back to product teams to shape the roadmap.
Develop production-ready coding agents and agentic workflows by integrating internal and open-weight models into JetBrains products. Design the agent loop, create evaluation suites, and establish feedback loops to improve model behavior based on real-world usage.
Build and ship production-ready AI-powered product features and LLM-based workflows from idea to deployment. Improve existing AI systems for quality, reliability, and latency while integrating capabilities into backend systems.
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Review and refine AI-generated content and workflows related to system operations and automation. Develop real-world use cases and provide actionable feedback to improve AI reasoning in operational scenarios.
Act as the central point of contact for AI initiatives, identifying use cases and implementing productive AI solutions from conception to deployment. Develop Agentic AI workflows, RAG systems, and automate processes using LLM APIs and cloud services.
Review and refine AI-generated outputs to ensure technical accuracy and real-world relevance in machine learning engineering. Create realistic ML scenarios and identify reasoning gaps to improve AI-powered systems.
Lead complex, end-to-end AI deployments and manage customer relationships throughout the engagement lifecycle. Architect multi-agent solutions, design personalized resource packs, and mentor junior engineers to ensure high-quality deployment standards.
You will build and integrate AI-powered features into production systems while improving the reliability, latency, and quality of existing AI workflows. The role involves taking ownership of the full development lifecycle, from conceptualizing ambiguous product ideas to deploying robust, production-ready software.
You will build and integrate AI-powered product features from concept to production while improving the reliability and performance of existing workflows. The role involves designing LLM-based systems, implementing validation logic, and maintaining high-quality AI outputs within a fast-paced startup environment.
Evaluate and analyze LLM performance while architecting and building inference and training pipelines. You will contribute to hands-on design, model training, and deployment strategies within a technical greenfield project.
You will build and improve agentic systems for complex tendering workflows and own the end-to-end delivery of AI features from model to front-end. Additionally, you will iterate on ranking, retrieval, and price prediction models while collaborating with cross-functional teams to drive metrics-led improvements.
You will develop, integrate, and operate production-ready AI modules, focusing on LLMs, speech processing, and retrieval-augmented generation. You will also build and maintain scalable ML pipelines while ensuring high performance, stability, and cost-efficiency in a production environment.
You will own the evaluation systems and quality standards for AI workflows, ensuring reliability and performance across the platform. Additionally, you will build and maintain monitoring, CI/CD integration, and production-ready AI workflows to support enterprise-scale operations.
As a Senior AI Engineer, you will develop intelligent features based on Natural Language Processing and generative AI, significantly contributing to the advancement of data-driven applications. You will be responsible for the entire development process of AI-supported applications, from concept to production deployment.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate cross-functionally with product and engineering teams.
We watch for new "AI Engineer" jobs and email you the matches. Free. Unsubscribe in one click.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate with product and engineering teams.
Develop cutting-edge GenAI solutions and own production rollouts of GenAI applications. Serve as a trusted technical advisor to customers and collaborate with cross-functional teams.
You will build and deploy full-stack applications that incorporate machine learning models and collaborate with cross-functional teams to deliver intelligent features. Your role will involve owning the full development lifecycle, from architecture and testing to deployment and monitoring.
Design, build, and ship production-grade ML models for high-impact use cases while leading model architecture and deployment strategies. Collaborate across teams to drive AI initiatives and mentor junior engineers.
You will design and deploy core AI systems that serve millions across Southeast Asia. This role involves leading technical execution, mentoring junior engineers, and contributing to hiring a high-performance AI team.
As a Founding AI Engineer, you will build and deploy full-stack applications that incorporate machine learning models and collaborate with cross-functional teams to deliver intelligent features. You will own the full development lifecycle, from architecture and testing to deployment and monitoring.
You will lead the full-stack development of the PR platform and build an end-to-end agentic system for PR workflows. Additionally, you will contribute to system architecture, database design, and the integration of self-learning AI components.
You will build and maintain features across the full stack, from initial product discussion through to release and ongoing maintenance. Additionally, you will collaborate with event experts to develop, evaluate, and refine AI-driven workflows and features.
You will lead the full-stack development of a PR platform and build an end-to-end agentic AI system to redefine the PR value chain. Additionally, you will contribute to system architecture, database management, and the integration of self-learning loops.
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You will design, build, and operate high-availability AI/ML platforms on Kubernetes, including GPU infrastructure and model-serving services. Additionally, you will develop MLOps/LLMOps workflows and provide technical leadership and consulting to clients on AI governance and performance optimization.
Build and ship AI-powered products, scalable Python and FastAPI backend services, and data pipelines, taking features from initial idea through deployment and production. Make architectural decisions, evaluate practical uses for generative AI, and own the reliability, observability, and performance of the systems you build.
You will design, build, and operate productive AI applications and agentic systems integrated into existing complex software landscapes. Your role involves technical ownership, ensuring system reliability, and guiding AI-driven solutions from prototype to production.
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