×
Hier anmelden um sich kostenlos auf Stellen zu bewerben oder Stellenanzeigen aufzugeben. X

Forward Deployed AI Engineer Munich, Bavaria, Germany

in 80331, München, Bayern, Deutschland
Unternehmen: Greenhouse Software, Inc.
Vollzeit position
Verfasst am 2026-09-27
Berufliche Spezialisierung:
  • Software Entwicklung
    Robotik, Künstliche Intelligenz Ingenieur, Maschinelles Lernen
Gehalts-/Lohnspanne oder Branchenbenchmark: 90000 - 130000 EUR pro Jahr EUR 90000.00 130000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Forward Deployed AI Engineer New Munich, Bavaria, Germany

Agile Robots SE is an innovative company with a clear mission: bringing intelligent robotic solutions to our customers. We combine the latest technology in the field of AI with powerful robotic systems — from industrial robot arms and mobile manipulators to humanoids — to solve tasks that classical automation cannot address.

At the heart of our offering is a versatile software platform for orchestrating complex robotic systems. It allows efficient customization for specific customer requirements: configuring systems, developing reusable skills, parameterizing processes, and executing tasks reliably in production. Learned models — from perception to end-to-end policies — are a core part of this platform.

Our solutions are deployed with international customers across a wide range of industries. Seamless integration and scalable deployment are at the core of our mission.

We are looking for a passionate Forward Deployed AI Engineer to bring state-of-the-art robot learning and computer vision models into real production environments. In this role, you will train, fine-tune, and deploy AI models directly on customer robots — from Vision-Language-Action models and diffusion policies to perception and grasp generation networks. You will become a trusted technical partner, turning customer challenges into robust, data-driven robotics applications.

The role is based in Munich, Germany.

Responsibilities
  • Deploy, fine-tune, and evaluate AI models on real robotic systems at customer sites — including Vision-Language-Action (VLA) models, diffusion policies, and other end-to-end learned policies
  • Adapt and train perception models for robotic applications, e.g. object detection, segmentation, and pose estimation based on YOLO, SAM, vision transformers, and self-supervised backbones such as DINOv2
  • Integrate and tune grasp generation models (e.g., Grasp Net, Dex-Net, Contact-Grasp Net) for bin picking and manipulation tasks
  • Build data pipelines for customer deployments: demonstration and teleoperation recording, dataset curation, annotation, training runs, and systematic evaluation of model performance
  • Bring models into production: optimize inference, deploy on edge and embedded hardware, and integrate models into our robotic software platform
  • Work closely with customers to understand technical requirements and translate them into robust, AI-driven robotics applications
  • Diagnose, troubleshoot, and resolve model, software, and system integration issues both remotely and on-site
  • Travel to international customer sites for workshops, deployments, training, and technical support (up to 40% travel)
  • Master's degree in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a related field — or equivalent practical experience
  • Minimum of four years of professional experience in machine learning, AI for robotics, or computer vision
  • Hands-on experience working with real robots — robot arms, mobile manipulators, grippers, cameras, and sensors — not only in simulation
  • Proven experience with end-to-end learned models for robotics (e.g., VLAs, diffusion policies, imitation or reinforcement learning policies), covering training, fine-tuning, and deployment
  • Strong programming skills in both Python and C++
  • Solid command of machine learning frameworks (e.g., PyTorch, Tensor Flow) and the full model lifecycle: data curation, training, evaluation, and deployment
  • Experience with modern computer vision models such as YOLO, SAM, vision transformers, and self-supervised backbones (e.g., DINOv2, CLIP)
  • Experience with learned grasp generation for manipulation (e.g., Grasp Net, Dex-Net, or comparable approaches)
  • Good understanding of robot (inverse) kinematics, coordinate transformations, and hand-eye calibration
  • Experience working…
Um Jobs auf dieser Seite anzusehen und sich zu bewerben, die Bewerbungen aus Ihrem Standort oder Land akzeptieren, klicken Sie unten auf den Button, um eine Suche zu starten.
(Wenn dieser Job tatsächlich in Ihrem Zuständigkeitsbereich liegt, verwenden Sie möglicherweise einen Proxy oder VPN, um auf diese Seite zuzugreifen. Um weiterzukommen, sollten Sie Ihre Verbindung zu einem anderen Mobilgerät oder PC wechseln).
 
 
 
Suchen Sie hier nach weiteren Stellen:
(nach Beruf, Fähigkeit)
Standort
Suchradius erweitern (Meilen)
0
200
Filter
Mindest-Bildungsgrad für die Stelle
Mindest-Berufserfahrung für die Stelle
Veröffentlicht in den letzten:
Gehalt