Senior GenAI Data Scientist (m/f/d)
Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating p
Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating p
Entwickelt und trainiert generative 3D-Weltmodelle und Diffusionsmodelle für Bild und Video, inklusive verteiltem Training und Produktivsetzung.
Master s degree or PhD in Computer Science, Information Systems, Robotics, Computer Vision, or a related field.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
define and own the data science and AI strategy across the organization - lead development and scaling of predictive and generative AI model
Wir schreiben dir, sobald eine neue geprüfte Stelle in München dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and simulation.
Bridge the gap: Develop and maintain the hardware abstraction layers that allow our higher-level autonomy modules to interact seamlessly with the physical robot.
As an AI Product Manager at Air Apps, you will be at the forefront of shaping AI-powered applications that enhance user experiences.
As an AI/ML Engineer, you will play a crucial role in designing, developing, and optimizing machine learning models to power our mobile applications.
is hands-on and code-heavy — you will work inside the same monorepo as the research team, mostly in Python, and should be as comfortable ref
At ARX Robotics, you will help advance the perception capabilities of next-generation unmanned ground vehicles.
Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvem
Entwickelt das Agents Kit, ein Mendix-SDK für Agenten und agentische Anwendungen, und arbeitet dazu mit Early-Adopter-Kunden in München.
Join our growing Roland Berger AI Lab as the technical backbone for designing secure, scalable (Gen)AI systems.
Huawei s Heisenberg Research Center in Munich is responsible for advanced technology research, architectural development, design and strateg
Baut die Sicherheitsschicht für autonome Agenten: Isolation, nachvollziehbare Ausführung, manipulationssichere Events und abgesicherte CI/CD-Pipeline.
will include: - Design and deliver end-to-end AI solutions, from proof of concept to production.
As an AI Deployment Strategist with Science Focus, you will drive the adoption and deployment of Mistral s AI solutions for science-heavy pr
You’ll be responsible for onboarding customers on our products, providing guidance on deployment and integration, and ensuring the best prod
Führt Kundenprojekte in Automotive, Luftfahrt und Energie durch und entwickelt ML- und Deep-Learning-Lösungen für Engineering-Daten.
You’ll take the lead in building the data intelligence dimension of Agileday’s AI product.
Huawei s Heisenberg Research Center in Munich is responsible for advanced technology research, architectural development, design and strateg
Role highlights: - Role: Forward Deployed AI Engineer - Department: Forward Deployed Engineering - Location: Germany - Reports to: VP, Forwa
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations. - Drive harness engineering practices across Data Science projects, creating agent-ready repositories, workflows, standards, and feedback loops that enable software engineering agents to generate, test, maintain, and review code reliably across AI, ML, and data products. - Develop and maintain knowledge integration pipelines, including RAG architectures, custom model fine-tuning, vector search, and other grounding methods to ensure our AI systems have the right context for accurate, relevant outputs. - Define evaluation strategies, build ground-truth datasets, and create automated test and monitoring setups to ensure stable long-term model performance and proactively detect issues such as drift or hallucination. - Collaborate with engineering, data, and product teams to integrate AI components into platforms, workflows, and customer-facing products, designing clean APIs, robust pipelines, and scalable deployment patterns. - Act as a hands-on expert for GenAI and agentic software engineering topics, mentoring peers, guiding solution architecture, and driving best practices in coding, testing, repository design, documentation, observability, and harness engineering across the team and beyond. - Experiment with new tools, models, and architectures, identify high-impact AI opportunities, and build prototypes that can scale into production-ready solutions. What you’ll bring: - A degree in computer science, data science, engineering, or a related field. - Experience designing maintainable, agent-ready engineering environments, including repository structures, coding standards, automated test suites, CI/CD workflows, documentation patterns, and feedback mechanisms that allow software engineering agents to safely generate, modify, review, and maintain code. - Experience with knowledge graphs, graph-based retrieval, semantic modelling, or ontology-driven knowledge representation is a plus. - Strong coding skills in Python and experience with robust software engineering practices. - Practical experience with RAG pipelines, vector databases, embeddings, or fine-tuning workflows. - Strong understanding of common challenges in AI development (ground-truth evaluation data, monitoring, integration complexity, model drift). - Experience deploying AI systems in a cloud environment and working with modern ML stacks. - Familiarity with MLOps, prompt engineering, or LLM-based application design. - Ability to explain complex AI topics in clear and actionable language to technical and non-technical stakeholders. - High motivation, ownership mentality, and a strong drive to build impactful AI products. - Fluency in English; German is a plus. A culture of growth.
With over 50 nationalities represented, we’re proud to welcome people of all backgrounds to our growing community, and we’re always finding new ways to help people feel welcomed and included. Here, you’ll have the tools, training and support you need to work in a way that suits you, learn new skills and reach your potential. For a career where you can drive our business and shape your future, apply now.
A career driven by you. Join AutoScout24 Group and experience life in the fast lane. We’re not just leading the market; we’re creating it.
We’re constantly innovating, evolving, and transforming things for our customers. We’re driven, ambitious, and determined to do our best work together. For a career that doesn’t stand still, where you can put your ideas in the driving seat and change the way the world moves, join our international community.
As Senior GenAI Data Scientist, you’ll join our Data Science organisation and drive the development of next-generation AI solutions across the company. You will take ownership of building agentic GenAI systems, integrating knowledge into models, and setting up strong evaluation and monitoring frameworks that ensure we deliver reliable, scalable, and high-value AI products. This position is permanent and located in Munich (Germany) or Toronto (Canada).
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Zur Originalanzeige128 geprüfte Stellen bei 79 Arbeitgebern, 10 davon ortsunabhängig. 73 in der KI-Entwicklung, 33 in Integration & Automatisierung.