21 geprüfte KI-Jobs in München
Wie wir sortierenAI Software Development Engineer - Neuromorphic Computing (m/f/d) (Fixed-Term)
If you re excited by the idea of building technologies that go beyond today s AI accelerators and helping define the future of computing, we
Computer Vision Engineer – Object Detection (m/f/d)
Research Scientist - World Models
Entwickelt und trainiert generative 3D-Weltmodelle und Diffusionsmodelle für Bild und Video, inklusive verteiltem Training und Produktivsetzung.
Research Scientist - 3D Diffusion
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
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Machine Learning & Cloud Infra Engineer
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and simulation.
AI Product Manager
As an AI Product Manager at Air Apps, you will be at the forefront of shaping AI-powered applications that enhance user experiences.
AI/ML Engineer
As an AI/ML Engineer, you will play a crucial role in designing, developing, and optimizing machine learning models to power our mobile applications.
Machine Learning Systems & Infrastructure Engineer
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
AI/ML Engineer (Leased Labor 18-months)
Huawei s Heisenberg Research Center in Munich is responsible for advanced technology research, architectural development, design and strateg
AI Deployment Strategist, Science - EMEA
As an AI Deployment Strategist with Science Focus, you will drive the adoption and deployment of Mistral s AI solutions for science-heavy pr
Applied AI Engineer, ML Infrastructure Engineer / Devops - EMEA
You’ll be responsible for onboarding customers on our products, providing guidance on deployment and integration, and ensuring the best prod
Forward Deployed Engineer for Robotics (m/f/d)
Agile Robots SE is an innovative company with a clear mission: bringing intelligent robotic solutions to our customers.
Field Application Engineer - AI Software & Hardware
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency.
Robot Learning Engineer
Definiert die Kamera-Erfassungsspezifikation für Manipulations-Trainingsdaten, baut das Evaluationsframework und trainiert erste Roboter-Policies auf eigenen Daten.
Forward Deployed AI Engineer (m/f/d)
is based in Munich, Germany.
Research Engineer - 3D Reconstruction
Entwickelt und verbessert 3D-Rekonstruktionsmethoden und Szenenrepräsentationen wie Gaussian Splats, von Optimierung pro Szene bis zu Feed-forward-Modellen.
ML Inference Engineer
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
AIoT Backend Developer
Du besprichst Requirements direkt mit dem Kunden, entwirfst darauf basierend technische Lösungen und arbeitest bei deren Implementierung mit
AIoT Fullstack Developer
Deine Leidenschaft für die Frontend- und Backend Entwicklung kannst du in unseren spannenden und innovativen Projekten im AIoT (AI und IoT)
im Bereich Data Intelligence
ARRK Engineering ist ein globaler Entwicklungspartner für die Automobil- und Mobilitätsindustrie und für innovative Produktentwicklung.
Das waren alle 21 Jobs zu dieser Auswahl.
AI Engineer Computer Vision & MLOps
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
Anforderungen
We re looking for a highly driven Computer Vision / ML Engineer to own the data, training, evaluation, and MLOps lifecycle for our camera-based perception models. In this role, you ll turn real and synthetic drone data into reproducible, validated model releases, building and operating the pipelines that connect collection, annotation, training, evaluation, and release. This is an ownership role where you ll work closely with robotics perception engineers, directly shaping how reliably our systems see and understand the world.
The day-to-day - Requirements definition: define clear objectives, interfaces, datasets, and release standards for deep learning tasks such as detection, segmentation, and depth - Data strategy: drive real-world and synthetic data collection campaigns covering edge cases, rare conditions, and class imbalance - Dataset integrity: build trusted, versioned, auditable datasets, maintaining lineage and preventing leakage across every model release - Model performance: develop, train, and benchmark detection, segmentation, and depth-estimation models for aerial imagery - Evaluation rigor: set a high bar for evaluation and failure analysis across range, altitude, illumination, and weather conditions - MLOps ownership: build and operate the end-to-end pipeline for versioning, reproducible training, experiment tracking, and CI/CD - Deliver production-ready model artifacts. Export and optimize models for ONNX and TensorRT, validate accuracy and runtime performance. You should apply if you - Computer vision depth: you have a deep understanding of CNN- and transformer-based architectures, training dynamics, and evaluation, with hands-on PyTorch experience - Dataset discipline: you re experienced building representative dataset splits, validating annotations, and conducting detailed failure analysis - MLOps experience: you have end-to-end production MLOps ownership, including experiment tracking, versioning, and CI/CD - Software engineering: you write clean, tested, maintainable code and make sound performance and algorithmic trade-offs - Track record: you bring 3+ years building and shipping computer-vision or ML systems with ownership across data, training, and evaluation - Education: you hold a degree in computer science, machine learning, or a related field – or equivalent hands-on experience that speaks louder than the diplom Nice to haves - Aerial vision: experience with drone imagery, small-object detection, or low-light and low-resolution data - Simulation expertise: hands-on experience with NVIDIA Isaac Sim, Omniverse, or other synthetic-data workflows - Inference optimization: experience exporting and optimizing models with ONNX and TensorRT on NVIDIA Jetson hardware
Das wird geboten
Real impact & ownership: Shape high-tech defense systems and take responsibility from day one. - Mission-driven environment: Work on technologies that matter for European security and sovereignty. - Competitive package: Competitive salary, EGYM Wellpass, corporate benefits, and equity options aligned with role and level. - Deep tech environment: Get hands-on experience with cutting-edge drone technology and real operational use cases. - Grow fast: Steep learning curve for juniors, strategic influence and leadership opportunities for seniors. - Startup mindset meets defence innovation: flat hierarchies, fast decisions, and space for your ideas. - Flexibility: Flexible hours, remote options, and relocation support. - Strong team: International, driven colleagues and a culture built on exchange, trust, and shared success.
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Zur OriginalanzeigeKI-Jobs in München
124 geprüfte Stellen bei 78 Arbeitgebern, 6 davon ortsunabhängig. 70 in der KI-Entwicklung, 32 in Integration & Automatisierung.