Forward Deployed AI Engineer

Agilerobotsse·Munich, Bavariasenior

En corto

→Ingeniero de IA desplegado en cliente, implementando modelos de visión y aprendizaje para robots reales.
→Trabajas directamente en sitios de clientes, entrenando, fine-tuneando y desplegando modelos como VLA y políticas de difusión.
→Destacado: viajes internacionales hasta un 40% para despliegues y soporte técnico en el terreno.

Conocimiento del idioma inglés (requisito mínimo)

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¿Qué piden?

✓Título de Máster en Robótica, Ciencia de la Computación, IA o campo relacionado (o experiencia equivalente)
✓4 años de experiencia profesional en ML, IA para robótica o visión por computadora
✓Experiencia práctica con robots reales (brazos, manipuladores móviles, sensores)
✓Experiencia comprobada con modelos end-to-end para robótica (VLA, diffusion policies, IRL, RL)
✓Habilidades sólidas en Python y C++
✓Conocimiento de frameworks como PyTorch, TensorFlow y el ciclo completo de modelos

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonC++PyTorchTensorFlowYOLOSAMvision transformersDINOv2CLIPGraspNet

¿A quién escribirle en Agilerobotsse?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

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., GraspNet, Dex-Net, Contact-GraspNet) 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) Essential Skills • 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, TensorFlow) 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., GraspNet, Dex-Net, or comparable approaches) • Good understanding of robot (inverse) kinematics, coordinate transformations, and hand-eye calibration • E

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